Search

Your search keyword '"Rula A."' showing total 2,785 results
Start Over Author "Rula A." Search Limiters Available in Library Collection
2,785 results on '"Rula A."'

1. Data Collection and Preprocessing in Web Usage Mining: Implementation and Analysis

Author

Mohammed Ali Mohammed, Rula A. Hamid, and Reem Razzaq AbdulHussein

Subjects
web usage mining, access log file, data collection, data preprocessing, Technology
Abstract

Data collection and data preprocessing are crucial stages in web usage mining, mainly because of the unstructured, diverse, and noisy nature of log data. During data collection, log file datasets are loaded and merged. Effective and comprehensive data preprocessing plays a vital role in ensuring the efficiency and scalability of algorithms used in the pattern discovery phase of web usage mining. This work aims to address these phases by introducing two innovative approaches. The first approach focuses on determining the device used for accessing the web, distinguishing between computers and mobile devices. The second approach aims to determine user sessions and complete paths by utilizing the referrer URL. The entire preprocessing pipeline has been implemented using the C# programming language, and the source code is available on GitHub at the following link: https://github.com/Mohammed91/Web-Usage-Mining.

Published
2024
Full Text
View/download PDF

2. Navigating Personal, Social, and Environmental Obstacles to Healthy Lifestyle in Jordanian Adolescents

Author

Rula A. Amr, Ahmed M. Al-Smadi, Nanda Alqutob, and Rand T. Akasheh

Subjects
Technology, Medicine, Science
Abstract

Conclusion: These barriers may contribute to increasing childhood obesity rates in Jordan. Future interventions should prioritize creating a supportive environment that respects cultural norms, emphasizing high-quality parks, nutrition and sports education, healthier food options, student motivation, and park visits. Community engagement is crucial for fostering healthier lifestyles among Jordanian youth.

Published
2025
Full Text
View/download PDF

3. Management of Uveitis Patients on Anti-TNF Agents Who Develop Demyelinating Disease – A Case Series

Author

Abel Hamdan, Sumit Sharma, Kimberly Baynes, Rula A. Hajj Ali, Careen Y. Lowder, and Sunil K. Srivastava

Subjects
Drugs, Immunology, Inflammation, Retina, Treatment medical, Ophthalmology, RE1-994
Abstract

Abstract Background/Aims Anti-tumor necrosis factor (Anti-TNF) agents have proven beneficial for the treatment of chronic non-infectious uveitis, yet rare neurological complications and demyelinating disease can occur with their use. Management of uveitis and neurological disease after developing these rare complications is not well understood. We sought to identify these specific cases and their outcomes through a retrospective observational case series. Methods Electronic Medical Record (EMR) chart review of 394 non-infectious uveitis patients on anti-TNF therapy focused on identifying patients seen by uveitis specialists at a single institution who were on anti-TNF therapy and had developed neurological symptoms. Cases were reviewed for subsequent management and outcomes of both their neurologic and ocular inflammatory disease. Results Five (5) patients were included following complaints of neurological symptoms while on anti-TNF therapy. Subsequent demyelinating diagnosis, acute treatment, and long-term course were described. All five patients continue to be inactive at around three years of anti-TNF discontinuation. Conclusion Unidentified rare neurological symptoms and demyelinating disease associated with the use of anti-TNF agents can be detrimental to patient treatment outcomes. Emphasis is given on possible avoidance and early identification of exacerbating underlying disease through a detailed neurologic history and use of imaging when suspicion is high. Patients may have no evidence of higher neurological risk prior to starting an anti-TNF treatment. Discontinuation of an anti-TNF agent and subsequent control of disease is possible with alternative immunosuppressive treatments.

Published
2024
Full Text
View/download PDF

4. Fuzzy Evaluation and Benchmarking Framework for Robust Machine Learning Model in Real-Time Autism Triage Applications

Author

Ghadeer Ghazi Shayea, Mohd Hazli Mohammed Zabil, A. S. Albahri, Shahad Sabbar Joudar, Rula A. Hamid, O. S. Albahri, A. H. Alamoodi, Idrees A. Zahid, and Iman Mohamad Sharaf

Subjects
2-Tuple linguistic Fermatean, Autism spectrum disorder, Triage, Selection, MCDM, Robust machine learning, Electronic computers. Computer science, QA75.5-76.95
Abstract

Abstract In the context of autism spectrum disorder (ASD) triage, the robustness of machine learning (ML) models is a paramount concern. Ensuring the robustness of ML models faces issues such as model selection, criterion importance, trade-offs, and conflicts in the evaluation and benchmarking of ML models. Furthermore, the development of ML models must contend with two real-time scenarios: normal tests and adversarial attack cases. This study addresses this challenge by integrating three key phases that bridge the domains of machine learning and fuzzy multicriteria decision-making (MCDM). First, the utilized dataset comprises authentic information, encompassing 19 medical and sociodemographic features from 1296 autistic patients who received autism diagnoses via the intelligent triage method. These patients were categorized into one of three triage labels: urgent, moderate, or minor. We employ principal component analysis (PCA) and two algorithms to fuse a large number of dataset features. Second, this fused dataset forms the basis for rigorously testing eight ML models, considering normal and adversarial attack scenarios, and evaluating classifier performance using nine metrics. The third phase developed a robust decision-making framework that encompasses the creation of a decision matrix (DM) and the development of the 2-tuple linguistic Fermatean fuzzy decision by opinion score method (2TLFFDOSM) for benchmarking multiple-ML models from normal and adversarial perspectives, accomplished through individual and external group aggregation of ranks. Our findings highlight the effectiveness of PCA algorithms, yielding 12 principal components with acceptable variance. In the external ranking, logistic regression (LR) emerged as the top-performing ML model in terms of the 2TLFFDOSM score (1.3370). A comparative analysis with five benchmark studies demonstrated the superior performance of our framework across all six checklist comparison points.

Published
2024
Full Text
View/download PDF

5. Prioritizing complex health levels beyond autism triage using fuzzy multi-criteria decision-making

Author

A. S. Albahri, Rula A. Hamid, Laith Alzubaidi, Raad Z. Homod, Khamis A. Zidan, Hassan Mubark, Ghadeer Ghazi Shayea, O. S. Albahri, and A. H. Alamoodi

Subjects
Autistic patients, Ranking, Complex emergency levels, Multi-criteria decision making, Fuzzy, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64
Abstract

Abstract This study delves into the complex prioritization process for Autism Spectrum Disorder (ASD), focusing on triaged patients at three urgency levels. Establishing a dynamic prioritization solution is challenging for resolving conflicts or trade-offs among ASD criteria. This research employs fuzzy multi-criteria decision making (MCDM) theory across four methodological phases. In the first phase, the study identifies a triaged ASD dataset, considering 19 critical medical and sociodemographic criteria for the three ASD levels. The second phase introduces a new Decision Matrix (DM) designed to manage the prioritization process effectively. The third phase focuses on the new extension of Fuzzy-Weighted Zero-Inconsistency (FWZIC) to construct the criteria weights using Single-Valued Neutrosophic 2-tuple Linguistic (SVN2TL). The fourth phase formulates the Multi-Attributive Border Approximation Area Comparison (MABAC) method to rank patients within each urgency level. Results from the SVN2TL-FWZIC weights offer significant insights, including the higher criteria values "C12 = Laughing for no reason" and "C16 = Notice the sound of the bell" with 0.097358 and 0.083832, indicating their significance in identifying potential ASD symptoms. The SVN2TL-FWZIC weights offer the base for prioritizing the three triage levels using MABAC, encompassing medical and behavioral dimensions. The methodology undergoes rigorous evaluation through sensitivity analysis scenarios, confirming the consistency of the prioritization results with critical analysis points. The methodology compares with three benchmark studies, using four distinct points, and achieves a remarkable 100% congruence with these prior investigations. The implications of this study are far-reaching, offering a valuable guide for clinical psychologists in prioritizing complex cases of ASD patients.

Published
2024
Full Text
View/download PDF

6. Retinoblastoma with and without Extraocular Tumor Extension

Author

Swathi Kaliki, MD, Vijitha S. Vempuluru, MD, Ido Didi Fabian, MD, Elhassan Abdallah, MD, Shehu U. Abdullahi, MD, Rula A. Abdulqader, MD, Aminatu A. Abdulrahaman, MD, Sherif Abouelnaga, MD, Dupe S. Ademola-Popoola, FMCOph, FWACS, Adedayo Adio, FWACS, Mahmoud A. Afifi, MD, Armin R. Afshar, MD, Priyanka Aggarwal, MD, Ada E. Aghaji, FMCOph MSc, Alia Ahmad, MRCPCH UK, Marliyanti N.R. Akib, MD, Adeseye M. Akinsete, MBBS, Lamis Al Harby, MD, Saleh A. Al Mesfer, MD, Mouroge H. Al Ani, MD, Silvia Alarcón Portabella, MD, Safaa A.F. Al-Badri, MD, Ana Patricia A. Alcasabas, MD, Saad A. Al-Dahmash, MD, Amanda Alejos, MD, Ernesto Alemany-Rubio, MD, Amadou I. Alfa Bio, MD, Yvania Alfonso Carreras, MD, Christiane E. Al-Haddad, MD, Hamoud H.Y. Al-Hussaini, MD, MSc, Amany M. Ali, MD, Donjeta B. Alia, MD, Mazin F. Al-Jadiry, MD, Usama Al-Jumaly, MD, Hind M. Alkatan, MD, Charlotta All-Eriksson, MD, PhD, Ali A.R.M. Al-Mafrachi, FIBMS, Argentino A. Almeida, MD, Khalifa M. Alsawidi, MD, Athar A.S.M. Al-Shaheen, MD, Entissar H. Al-Shammary, MD, Doreen Amankwaa-Frempong, MBChB, Primawita O. Amiruddin, MD, Inggar Armytasari, MD, Nicholas J. Astbury, FRCS, FRCOphth, Hatice T. Atalay, MD, Eda Ataseven, MD, La-ongsri Atchaneeyasakul, MD, Rose Atsiaya, OCO, Rudolf Autrata, MD, PhD, Julia Balaguer, MD, PhD, Ruhengiz Balayeva, PhD, Honorio Barranco, MD, PhD, Paulina Bartoszek, MD, Katarina Bartuma, MD, PhD, Covadonga Bascaran, MD, MSc, Nikolaos E. Bechrakis, MD, Maja Beck Popovic, MD, Ainura S. Begimkulova, MD, Sarra Benmiloud, MD, Rokia C. Berete, MD, PhD, Jesse L. Berry, MD, Anirban Bhaduri, MD, Sunil Bhat, MBBS, MD, Arpita Bhattacharyya, MD, Eva M. Biewald, MD, Elaine Binkley, MD, Sharon Blum, MD, Nadia Bobrova, MD, H. Culver Boldt, MD, Maria Teresa B.C. Bonanomi, MD, PhD, Gabrielle C. Bouda, MD, Hédi Bouguila, MD, PhD, Rachel C. Brennan, MD, Bénédicte G. Brichard, MD, PhD, Jassada Buaboonnam, MD, Aléine Budiongo, MD, Matthew Burton, FRCOphth, Patricia Calderón-Sotelo, MD, Doris A. Calle Jara, MD, Jayne E. Camuglia, FRANZCO, Miriam R. Cano, MD, MSc, Michael Capra, FRCPI, Shani Caspi, MD, Nathalie Cassoux, MD, PhD, Guilherme Castela, MD, Luis Castillo, MD, Jaume Català-Mora, MD, PhD, Isabel Caviedes, MD, Arthika Chandramohan, MD, Guillermo L. Chantada, MD, PhD, Shabana Chaudhry, MD, Bhavna Chawla, MD, Wensi Chen, MD, Faraja S. Chiwanga, MSc, Tsengelmaa Chuluunbat, MD, PhD, Krzysztof Cieslik, MD, Antony Clark, FRANZCO, Ruellyn L. Cockcroft, MB ChB , M Med Paed, Codruta Comsa, MD, Maria G. Correa Llano, MD, Timothy W. Corson, PhD, Line Couitchere, MD, Kristin E. Cowan-Lyn, MD, MBBS, Monika Csóka, MD, PhD, Wantanee Dangboon, MD, Anirban Das, MD, Pranab Das, MD, Sima Das, MS, Jacquelyn M. Davanzo, BSN, BSPH, Alan Davidson, MBChB, MPhil, Sonia De Francesco, MD, Patrick De Potter, MD, PhD, Karina Q. Delgado, MD, PhD, Hakan Demirci, MD, Laurence Desjardins, MD, Rosdali Y. Diaz Coronado, MD, Helen Dimaras, PhD, Andrew J. Dodgshun, M Phil, Carla R. Donato Macedo, MD, Monica D. Dragomir, MD, PhD, Yi Du, MD, Magritha Du Bruyn, MD, Johannes P. Du Plessis, MMed (Paed), Gagan Dudeja, MBBS, MS, Katrin Eerme, MD, I Wayan Eka Sutyawan, MD, Asmaa El Kettani, MD, Amal M. Elbahi, MD, James E. Elder, MBBS, Alaa M. Elhaddad, MD, PhD, Moawia M.A. Elhassan, MD, Mahmoud M. Elzembely, MD, Connor Ericksen, MD, Vera A. Essuman, FWACS, Ted Grimbert A. Evina, MD, Ifeoma R. Ezegwui, FMCOph, FWACS, FAEH, Zehra Fadoo, MBBS, Adriana C. Fandiño, MD, Mohammad Faranoush, MD, Oluyemi Fasina, FWACS, Delia D.P.G. Fernández, MSc, Ana Fernández-Teijeiro, MD, PhD, Allen Foster, FRCOphth, Shahar Frenkel, MD, PhD, Ligia D. Fu, MD, Soad L. Fuentes-Alabi, MD, MPH, Juan L. Garcia, MSc, David García Aldana, MD, Henry N. Garcia Pacheco, MD, Jennifer A. Geel, MBChB, MMed, Fariba Ghassemi, MD, Ana V. Girón, MD, Marco A. Goenz, MD, Aaron S. Gold, OD, Hila Golberg, MD, Glen A. Gole, MD, FRANZCO, Nir Gomel, MD, Efren Gonzalez, MD, Graciela Gonzalez Perez, MD, Liudmira González-Rodríguez, MD, Malka Gorfine, PhD, Jaime Graells, MD, Pernille A. Gregersen, MD, Nathalia D.A.K. Grigorovski, MD, Koffi M. Guedenon, MD, D Sanjeeva Gunasekera, MD, Ahmet K. Gündüz, MD, Himika Gupta, MD, Sanjiv Gupta, MS, Vineeta Gupta, MD, Theodora Hadjistilianou, MD, Patrick Hamel, MD, Syed A. Hamid, FCPS, Norhafizah Hamzah, MSc, Eric D. Hansen, MD, J William Harbour, MD, M. Elizabeth Hartnett, MD, Murat Hasanreisoglu, MD, Sadiq Hassan, MD, FWACS, Shadab Hassan, FRCS, FCPS, Wojciech Hautz, MD, Huda A. Haydar, CHD, Stanislava Hederova, MD, Laila Hessissen, MD, Hoby Lalaina, MD, Suradej Hongeng, MD, Diriba F. Hordofa, MD, G. Baker Hubbard, MD, Marlies Hummlen, MD, Kristina Husakova, MD, Allawi N. Hussein Al-Janabi, MD, Affiong A. Ibanga, MB.BCh, FMCOph, Russo Ida, MD, Vesna R. Ilic, MD, Ziyavuddin Islamov, MD, Vivekaraj Jairaj, DNB, Teyyeb A. Janjua, MD, FCPS, FRCSEd, Irfan Jeeva, FRCOphth, Xunda Ji, MD, Dong Hyun Jo, MD, PhD, Michael M. Jones, MD, PhD, FRANZCO, Theophile B. Amani Kabesha, MD, PhD, Rolande L. Kabore, MD, Abubakar Kalinaki, MD, Pius Kamsang, MD, Mehmet Kantar, MD, Noa Kapelushnik, MD, Tamar Kardava, PhD, Rejin Kebudi, MD, Jonny Keomisy, MD, Tomas Kepak, MD, Petra Ketteler, MD, Zohora J. Khan, MD, Hussain A. Khaqan, MD, Vikas Khetan, FRCS, FACS, Alireza Khodabande, MD, Zaza Khotenashvili, MD, Jonathan W. Kim, MD, Jeong Hun Kim, MD, PhD, Hayyam Kiratli, MD, Tero T. Kivelä, MD, Artur Klett, MD, PhD, Irem Koç, MD, Jess Elio Kosh Komba Palet, MD, Dalia Krivaitiene, MD, PhD, Mariana Kruger, Mmed Paed, PhD, Kittisak Kulvichit, MD, Mayasari W. Kuntorini, MD, Alice Kyara, BA, Geoffrey C. Lam, FRANZCO, Scott A. Larson, MD, Slobodanka Latinović, MD, PhD, Kelly D. Laurenti, MD, Yotam Lavi, MD, PhD, Alenka Lavric Groznik, MD, Amy A. Leverant, MD, Cairui Li, MD, Kaijun Li, MD, Ben Limbu, MD, Chun-Hsiu Liu, MD, Quah Boon Long, FRCS (Ed), MMed ( Ophth), FAMS, Juan P. López, MD, Robert M. Lukamba, MD, Sandra Luna-Fineman, MD, Delfitri Lutfi, MD, Lesia Lysytsia, MD, Shiran Madgar, MD, George N. Magrath, MD, Amita Mahajan, MD, Puja Maitra, MD, Erika Maka, MD, Emil K. Makimbetov, MD, Azza M.Y. Maktabi, MD, Carlos Maldonado, MD, Ashwin Mallipatna, MD, Rebecca Manudhane, MD, Lyazat Manzhuova, MD, Nieves Martín Begue, MD, PhD, Sidra Masud, MBBS, Ibrahim O. Matende, MD, M. Med (Oph), Clarissa C.D.S. Mattosinho, MD, Marchelo Matua, BAPH, Ismail Mayet, MD, Freddy B. Mbumba, MD, MMed Paed, John D. McKenzie, MD, Azim Mehrvar, MD, Aemero A. Mengesha, MD, Vikas Menon, MD, Gary John V.D.D. Mercado, MD, Marilyn B. Mets, MD, Edoardo Midena, MD, PhD, Audra Miller, MD, Divyansh K.C. Mishra, DNB, Furahini G. Mndeme, MD, Ahmed A. Mohamedani, FRCPath, Mona T. Mohammad, MD, FRCS, Annette C. Moll, MD, PhD, Margarita M. Montero, MD, Claude Moreira, MD, PhD, Prithvi Mruthyunjaya, MD, MHS, Mchikirwa S. Msina, MMed Ophth, Gerald Msukwa, MMed Ophth, Sangeeta S. Mudaliar, DNB Pediatric, Hassan Muhammad, MD, Kangwa I. Muma, MMed Ophth, FCOphth, Francis L. Munier, MD, Timothy G. Murray, MD, MBA, Kareem O. Musa, FWACS, FMCOphth, FICO, Asma Mushtaq, MD, Anne A. Musika, MD, Hamzah Mustak, MD, Tajudeen Mustapha, MBBS, FWACS, Okwen M. Muyen, MD, Khumo H. Myezo, Msc, Gita Naidu, MMed Paed, PhD, Natasha Naidu, MBCHB, FCS Ophthalmol, Akshay Gopinathan Nair, MD, Sundaram Natarajan, FRCS, Larisa Naumenko, MD, PhD, Paule Aïda Ndoye Roth, MD PhD, Yetty M. Nency, MD, Vladimir Neroev, MD, PhD, Yvonne Ng, MBChB ( Auckland) , FRANZCO, Marina Nikitovic, MD, PhD, Elizabeth D. Nkanga, FMCOph, Henry E. Nkumbe, MD, Marcel N. Numbi, MD, Kalle Nummi, MD, Murtuza Nuruddin, FRCS, Mutale Nyaywa, MD, MMed Ophth, FCOphth, Chinsisi Nyirenda, MD, Ghislaine Obono-Obiang, MD, Scott C.N. Oliver, MD, Joaquin Ooporto, MD, Miriam Ortega-Hernández, MD, Alexander Oscar, MD, Diego Ossandon, MD, Halimah Pagarra, MD, PhD, Vivian Paintsil, FWACP, Luisa Paiva, MD, Mahesh Shanmugam Palanivelu, FRCSED, Ruzanna Papyan, MD, Raffaele Parrozzani, MD, PhD, Claudia R. Pascual Morales, MD, Katherine E. Paton, MD, FRCSC, Jacob Pe'er, MD, Jesús Peralta Calvo, MD, Sanja Perić, MD, PhD, Chau T.M. Pham, MD, Remezo Philbert, MD, David A. Plager, MD, Pavel Pochop, MD, PhD, Rodrigo A. Polania, MD, Vladimir Polyakov, MD, Jimena Ponce, MD, Ali O. Qadir, MD, Seema Qayyum, FCPS, Jiang Qian, MD, Ardizal Rahman, MD, Purnima Rajkarnikar, MD, Rajesh Ramanjulu, MD, Aparna Ramasubramanian, MD, Marco A. Ramirez-Ortiz, MD, MPH, Jasmeen K. Randhawa, BA, Léa Raobela, MD, Riffat Rashid, MS, M. Ashwin Reddy, FRCOphth, Lorna A. Renner, FRCPCH (UK), David Reynders, MD, Dahiru Ribadu, FMCOph, Petra Ritter-Sovinz, MD, Anna Rogowska, MD, Duangnate Rojanaporn, MD, Livia Romero, MD, Soma R. Roy, DCO, Raya H. Saab, MD, Svetlana Saakyan, MD, PhD, Ahmed H. Sabhan, MD, Mandeep S. Sagoo, FRCS (Ed), Azza M.A. Said, MD, Rohit Saiju, MD, Beatriz Salas, MD, Sonsoles San Román Pacheco, MD, Gissela L. Sánchez, MD, Alma Janeth Sanchez Orozco, MD, Phayvanh Sayalith, MD, Trish A. Scanlan, MRCPI, MSc, Christoph Schwab, MD, Ahad Sedaghat, MD, Rachna Seth, DNB MNAMS, Mariana Sgroi, MD, Ankoor S. Shah, MD, PhD, Shawkat A. Shakoor, MS, Manoj K. Sharma, MD, Sadik T. Sherief, MD, Carol L. Shields, MD, David Sia, MB ChB, FRANZCO, Sorath Noorani Siddiqui, MD, Sidi Sidi cheikh, MD, PhD, Sónia Silva, MD, Arun D. Singh, MD, Usha Singh, MS, Penny Singha, MD, Rita S. Sitorus, MD, PhD, Alison H. Skalet, MD, PhD, Hendrian D. Soebagjo, MD, PhD, Tetyana Sorochynska, MD, PhD, Grace Ssali, MD, Andrew W. Stacey, MD, Sandra E. Staffieri, PhD, Erin D. Stahl, MD, David M. Steinberg, PhD, David K. Stones, MBChB, FCPaed, Caron Strahlendorf, MD, Maria Estela Coleoni Suarez, MD, Sadia Sultana, FCPS, Xiantao Sun, MD, Rosanne Superstein, MD, Eddy Supriyadi, MD, PhD, Supawan Surukrattanaskul, MD, Shigenobu Suzuki, MD, PhD, Karel Svojgr, MD, PhD, Fatoumata Sylla, MD, Gevorg Tamamyan, MD, PhD, Deborah Tan, MBBS, Alketa Tandili, MD, PhD, Jing Tang, MD, Fanny F. Tarrillo Leiva, MD, Maryam Tashvighi, MD, Bekim Tateshi, MD, PhD, Kok Hoi Teh, MD, Edi S. Tehuteru, MD, Luiz F. Teixeira, MD, Manca Tekavcic Pompe, MD, PhD, Abdullah Dahan M. Thawaba, MD, Tuyisabe Theophile, MSc, Helen Toledano, MBChB, Doan L. Trang, MD, Fousseyni Traoré, MD, Devjyoti Tripathy, MD, Samuray Tuncer, MD, Harba Tyau-Tyau, MD, Ali B. Umar, MD, FMCPath, Emel Unal, MD, Ogul E. Uner, BA, Steen F. Urbak, MD, PhD, Tatiana L. Ushakova, MD, Rustam H. Usmanov, MD, Sandra Valeina, MD, Paola Valente, MD, Milo van Hoefen Wijsard, MD, Jacqueline Karina Vasquez Anchaya, MD, Leon O. Vaughan, FRCS (Ed), Nevyana V. Veleva-Krasteva, MD, PhD, Nishant Verma, MD, Andi A. Victor, MD, PhD, Maris Viksnins, MD, Edwin G. Villacís Chafla, MD, Victor M. Villegas, MD, Victoria Vishnevskia-Dai, MD, Keith Waddell, DM, FRCP, FRCS, FRCOphth, Amina H. Wali, MD, FMCOph Nigeria, Yi-Zhuo Wang, MD, Nutsuchar Wangtiraumnuay, MD, FICO, Julie A. Wetter, MMed Rad Onc, FCRad Onc, Widiarti P. Riono, MD, Matthew W. Wilson, MD, Amelia D.C. Wime, MD, Atchareeya Wiwatwongwana, MD, Damrong Wiwatwongwana, MD, Charlotte Wolley Dod, MD, Emily S. Wong, FCOphth HK, FHKAM, Phanthipha Wongwai, MD, PhD, Si-qi Wu, MSc, Daoman Xiang, MD, PhD, Yishuang Xiao, MSc, Bing Xu, MD, Kang Xue, MD, Antonio Yaghy, MD, Jason C. Yam, FRCSEd, Huasheng Yang, MD, Jenny M. Yanga, MD, Muhammad A. Yaqub, MD, FCPS, FRCSEd, Vera A. Yarovaya, MD, Andrey A. Yarovoy, MD, PhD, Huijing Ye, MD, Roberto I. Yee, MD, Yacoub A. Yousef, MD, Putu Yuliawati, MD, Arturo M. López, MD, Ekhtelbenina Zein, MD, Yi Zhang, MD, PhD, Katsiaryna Zhilyaeva, MD, Nida Zia, MBBS, MCPS, Othman A.O. Ziko, MD, PhD, Marcia Zondervan, MBA, Sabrina Schlüter, MD, and Richard Bowman, FRCOphth

Subjects
External beam radiotherapy, Extraocular extension, Multimodal treatment, Retinoblastoma, Tumor, Ophthalmology, RE1-994
Abstract

Purpose: To study the treatment and outcomes of children with retinoblastoma (RB) with extraocular tumor extension (RB-EOE) and compare them with RB without extraocular tumor extension (RB-w/o-EOE). Design: Multicenter intercontinental collaborative prospective study from 2017 to 2020. RB-EOE cases included those with overt orbital tumor extension in treatment-naive patients. Cases with microscopic orbital extension detected postenucleation were excluded from the study. Participants: A total of 319 children with RB-EOE and 3116 children with RB-w/o-EOE. Intervention: Chemotherapy, enucleation, exenteration, radiotherapy. Main Outcome Measures: Systemic metastasis and death. Results: Of the 3435 RB patients included in this study, 309 (9%) were from low-income countries (LIC), 1448 (42%) from lower-middle income, 1012 (29%) from upper-middle income, and 666 (19%) patients from high-income countries. There was an inverse relationship between the percentage of RB-EOE and national income level, with 96 (31%) patients from LIC, 197 (6%) lower-middle income, 20 (2%) upper-middle income, and 6 (1%) patients from high-income countries (P = 0.0001). The outcomes were statistically significant for RB-EOE compared with RB-w/o-EOE: systemic metastasis (32% vs. 4% respectively; P = 0.0001) and metastasis-related death (63% vs. 6% respectively; P = 0.0001). Multimodal treatment was the most common form of treatment (n = 177; 54%) for RB-EOE, with most cases undergoing a combination of intravenous chemotherapy and enucleation (n = 97; 30%). Adjuvant external beam radiotherapy (EBRT) after surgery (enucleation/orbital exenteration) was given in only 68 (21%) cases. Kaplan–Meier analysis for systemic metastasis and metastasis-related death in RB-EOE was 28% and 57% at 1 year, 29% and 60% at 2 years, and 29% and 61% at 3 years, respectively. Cox regression analysis revealed that the risk of death from RB-EOE was greater in patients aged >4 years than

Published
2025
Full Text
View/download PDF

7. Understanding the Association of Self-Efficacy, Mood, and Demographics with Physical Activity in Syrian and Iraqi Refugees: A Cross-Sectional Study in Jordan

Author

Rula A. Amr, Ahmed M. Al-Smadi, Rula A. Deiranieh, Romel A. Amr, Amal H. Mayyas, and Rand T. Akasheh

Subjects
Technology, Medicine, Science
Abstract

Objective. This cross-sectional study aimed at investigating the influence of sociodemographic factors on physical activity among Syrian and Iraqi refugees in Jordan. In addition, it sought to determine the predictive ability of self-efficacy and mood in relation to the level of physical activity in this population. Methods. A convenient sample of refugees residing in Jordanian cities was collected. Participants completed a self-administered questionnaire pack consisting of a demographic data sheet, a physical activity level questionnaire, the Brunel Mood Scale, and the General Self-Efficacy Scale. Descriptive analysis was used to analyze demographic details, while the chi-square test examined the association between physical activity and demographic factors. The independent t-test assessed differences in self-efficacy and mood subscales in relation to physical activity. Logistic regression analysis was employed to identify potential predictors of the two categories of physical activity. Results. Most participants reported low levels of physical activity. The frequency of moderate-to-high physical activity was higher in male participants, those with higher education, better health, and higher income. Compared to participants of low physical activity, those in the moderate-to-high physical activity category expressed significantly higher mean score of self-efficacy but lower mean scores of tension, depression, anger, vigor, fatigue, and confusion, indicating better mood. The logistic regression analysis for physical activity indicated that the model was significant for education, income, good health perception, self-efficacy, and one mood subscale (vigor), with these variables collectively accounting for 11–18% of the variance (P value

Published
2023
Full Text
View/download PDF

8. Intelligent triage method for early diagnosis autism spectrum disorder (ASD) based on integrated fuzzy multi-criteria decision-making methods

Author

Shahad Sabbar Joudar, A.S. Albahri, and Rula A. Hamid

Subjects
Autism, ASD, Triage, Fuzzy Delphi, MCDM, FWZIC, Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Background: Autism spectrum disorder (ASD) symptoms and severity levels vary from patient to patient, so treatment and healthcare will vary. However, little attention has been given to developing an autistic triage method for ASD patients concerning four issues: hybrid triage criteria, multi-selection criteria problems, criteria importance, and trade-off based on the inverse relationship between autistic criteria. Therefore, this study aims to develop a new method for triaging ASD patients and classifying them according to their severity of disorder using Fuzzy Multi-Criteria Decision Making (fMCDM) methods. Methods: Two methodology phases have been conducted: the first phase is to identify and preprocess the ASD dataset, including 988 autistic patients with 42 medical and Sociodemographic criteria. In the second phase, two fMCDM methods were used to develop the triage method. The fuzzy Delphi Method (FDM) is used to select the most influential criteria among the 42 based on thirteen psychologists in the psychological field. Then Fuzzy-Weighted Zero-Inconsistency (FWZIC) is used to assign weights to the important criteria according to four psychologists' opinions. Accordingly, the Processes for Triaging Autism Patients (PTAP) method has been developed for the first time for triaging and classifying patients into three severity levels: minor, moderate, and urgent. Results: For the preprocessed phase, 538 out of 988 patients were obtained as a new ASD dataset underwent data cleaning to capture only autism patients. For the second phase, the FDM results have selected 19 out of 42 criteria and can control the bias of psychologists' opinions, FWZIC has assigned the appropriate weights for the 19 criteria, and the PTAP method triages the 538 patients into three severity levels: 36 minor injuries, 432 moderate injuries, and 70 urgent injuries. More complex statistical analyses have been presented using MedCalc statistical software. Three physicians in the psychological field gave their subjective judgements for the diagnosis of 46 random samples of patients. The sensitivity results were 86.67%, 80%, and 90.91%, while the specificity results were 93.55%, 88.46%, and 94.29% for urgent, moderate, and minor levels, respectively. In addition, the accuracy was 91.30% for urgent, 84.78% for moderate, and 93.48% for minor. This assessment led to a deduction that a proposed ASD triage method can be applied with high performance. Conclusions: The developed triage method can be used for early autism diagnosis application and support clinical treatment utilizing the advantages of fMCDM techniques of multidimensional criteria. Four medical criteria were selected from the psychologists, while Sociodemographic acquired high attention with 15 selected criteria. For the correlation analysis of the 19 used criteria, the ‘Wave’ criterion has the highest correlation with the triage level and obtained 0.4523. On the contrary, the “Pointing with the index finger” criterion has the lowest correlation and obtained −0.0542. Limitations and future works have also been reported in this study. The study confirms the efficacy of the proposed triage method compared with previous studies in five comparative points with 100%.

Published
2023
Full Text
View/download PDF

9. Outcomes Following Acute Coronary Syndrome in Patients With and Without Rheumatic Immune‐Mediated Inflammatory Diseases

Author

Heba Wassif, Marwan Saad, Rajul Desai, Rula A. Hajj‐Ali, Venu Menon, Pulkit Chaudhury, Michael Nakhla, Rishi Puri, Sameer Prasada, Grant W. Reed, Khaled Ziada, Samir Kapadia, Milind Desai, and Amgad Mentias

Subjects
immune medicated inflammatory diseases, myocardial infarction, rheumatoid arthritis, systemic lupus, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Rheumatic immune mediated inflammatory diseases (IMIDs) are associated with high risk of acute coronary syndrome. The long‐term prognosis of acute coronary syndrome in patients with rheumatic IMIDs is not well studied. Methods and Results We identified Medicare beneficiaries admitted with a primary diagnosis of myocardial infarction (MI) from 2014 to 2019. Outcomes of patients with MI and concomitant rheumatic IMIDs including systemic lupus erythematosus, rheumatoid arthritis, systemic sclerosis, dermatomyositis, or psoriasis were compared with propensity matched control patients without rheumatic IMIDs. One‐to‐three propensity‐score matching was done for exact age, sex, race, ST‐segment–elevation MI, and non–ST‐segment–elevation MI variables and greedy approach on other comorbidities. The study primary outcome was all‐cause mortality. The study cohort included 1 654 862 patients with 3.6% prevalence of rheumatic IMIDs, the most common of which was rheumatoid arthritis, followed by systemic lupus erythematosus. Patients with rheumatic IMIDs were younger, more likely to be women, and more likely to present with non–ST‐segment–elevation MI. Patients with rheumatic IMIDs were less likely to undergo coronary angiography, percutaneous coronary intervention or coronary artery bypass grafting. After propensity‐score matching, at median follow up of 24 months (interquartile range 9–45), the risk of mortality (adjusted hazard ratio [HR], 1.15 [95% CI, 1.14–1.17]), heart failure (HR, 1.12 [95% CI 1.09–1.14]), recurrent MI (HR, 1.08 [95% CI 1.06–1.11]), and coronary reintervention (HR, 1.06 [95% CI, 1.01–1.13]) (P

Published
2022
Full Text
View/download PDF

10. The Degree of Satisfaction of Multicultural Non-Native Speakers of Arabic with a Training Program: A Case of Faculty Members

Author

Khalid M. A. Sheirah, Ahmad Tawalbeh, and Rula Abu-Elrob

Abstract

This study aimed to identify the effectiveness of training on non-native speakers of Arabic at a university in Saudi Arabia from their point of view by determining the degree of their satisfaction in terms of four aspects: benefits of the offered training, trainers' performance, organizational effectiveness of the training program and the difficulties encountered by the trainees during training. The study examined whether there are differences in the averages of the trainees' responses according to the number of their previous training courses. The surveyed sample consisted of 29 trainees chosen by the intentional method. To pursue the aim of the study, both quantitative and qualitative designs were used. A questionnaire consisting of 24 items was developed and the descriptive analytical method was used.? The results showed that the average responses of the trainees in the areas of the scale as a whole were high according to the statistical standards followed in the study with an arithmetic average of (3.88). The benefit and the organization aspects of the training course received an arithmetic average of (4.63), the trainer's performance came next with an average of (4.61). In the last place is the aspect of difficulties with an average of 1.67, which is at a weak level. The study also found that there are no significant differences between the trainees' responses to the first three aspects according to the number of previous training courses the trainees attended. ?However, there are statistically significant differences for the fourth aspect 'difficulties encountered by the trainees', as the value of (f) is (5.34). The study offers insights into the usefulness of holding such a training program for refining the skills of the trainees and enhancing their teaching strategies to create a better classroom environment.

Published
2024

11. Diagnosis-Based Hybridization of Multimedical Tests and Sociodemographic Characteristics of Autism Spectrum Disorder Using Artificial Intelligence and Machine Learning Techniques: A Systematic Review

Author

M. E. Alqaysi, A. S. Albahri, and Rula A. Hamid

Subjects
Medicine
Abstract

Autism spectrum disorder (ASD) is a complex neurobehavioral condition that begins in childhood and continues throughout life, affecting communication and verbal and behavioral skills. It is challenging to discover autism in the early stages of life, which prompted researchers to intensify efforts to reach the best solutions to treat this challenge by introducing artificial intelligence (AI) techniques and machine learning (ML) algorithms, which played an essential role in greatly assisting the medical and healthcare staff and trying to obtain the highest predictive results for autism spectrum disorder. This study is aimed at systematically reviewing the literature related to the criteria, including multimedical tests and sociodemographic characteristics in AI techniques and ML contributions. Accordingly, this study checked the Web of Science (WoS), Science Direct (SD), IEEE Xplore digital library, and Scopus databases. A set of 944 articles from 2017 to 2021 is collected to reveal a clear picture and better understand all the academic literature through a definitive collection of 40 articles based on our inclusion and exclusion criteria. The selected articles were divided based on similarity, objective, and aim evidence across studies. They are divided into two main categories: the first category is “diagnosis of ASD based on questionnaires and sociodemographic features” (n=39). This category contains a subsection that consists of three categories: (a) early diagnosis of ASD towards analysis, (b) diagnosis of ASD towards prediction, and (c) diagnosis of ASD based on resampling techniques. The second category consists of “diagnosis ASD based on medical and family characteristic features” (n=1). This multidisciplinary systematic review revealed the taxonomy, motivations, recommendations, and challenges of diagnosis ASD research in utilizing AI techniques and ML algorithms that need synergistic attention. Thus, this systematic review performs a comprehensive science mapping analysis and identifies the open issues that help accomplish the recommended solution of diagnosis ASD research. Finally, this study critically reviews the literature and attempts to address the diagnosis ASD research gaps in knowledge and highlights the available ASD datasets, AI techniques and ML algorithms, and the feature selection methods that have been collected from the final set of articles.

Published
2022
Full Text
View/download PDF

12. Beirut Port Blast: Use of Electronic Health Record System During a Mass Casualty Event

Author

Hitti, Eveline, Hadid, Dima, Saliba, Miriam, Sadek, Zouhair, Jabbour, Rima, Antoun, Rula, and El Sayed, Mazen

Subjects
Disaster Response, Emergency Preparedness Plan, Mass Casualty Incidents, Electronic Medical Records, Electronic Health Records, disaster response, Emergency Preparedness Plan, Mass Casualty Incidents, Electronic Medical Records
Abstract

Introduction: Emergency departments (ED) play a central role in defining the effectiveness and quality of the overall hospital’s mass casualty incident (MCI) response. The use of electronic health records (EHR) in hospital settings has been rapidly growing globally. There is, however, a paucity of literature on the use and performance of EHR during MCIs.Methods: In this study we aimed to describe EHR use, as well as the challenges and lessons learnt in response to the 2020 explosion in the Port of Beirut, Lebanon, during which the hospital received over 360 casualties.Results: Information technology support, reducing EHR system restrictions, cross-function training, focus on registration and patient identification, patient flow and tracking, mobility and bedside access, and alternate sites of care are all important areas to focus on during emergency/disaster response planning.Conclusion: Innovative solutions that help address logistical challenges for different aspects of the disaster response are needed.

Published
2024

14. Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart

Author

Read, David F., Booth, Gregory T., Daza, Riza M., Jackson, Dana L., Gladden, Rula Green, Srivatsan, Sanjay R., Ewing, Brent, Franks, Jennifer M., Spurrell, Cailyn H., Gomes, Anne Roshella, O’Day, Diana, Gogate, Aishwarya A., Martin, Beth K., Larson, Haleigh, Pfleger, Christian, Starita, Lea, Lin, Yiing, Shendure, Jay, Lin, Shin, and Trapnell, Cole

Published
2024
Full Text
View/download PDF

21. Enhancing the notification system for surveillance of infectious diseases in Qatar during the FIFA World Cup 2022: project overview

Author

Ibrahim, Wafa, Himatt, Sayed, Heikal, Sara, Al Shamali, Maha, Jabbar, Raihana, Elshareif, Tasneem, Bakiri, Agnes, Mahmoud, Montaha, Shami, Rula, Saeed, Hanaa, Shami, Ghaydah Al, Omer, Douaa, Barakat, Esraa, Mahadoon, Lylu, Elshaikh, Taysser, Rahma, Rania, Omer, Entesar, Elbourdiny, Aiman, Al Romaihi, Hamad, Al Thani, Mohamed, and Sallam, Mohamed

Published
2024
Full Text
View/download PDF

24. School-Based Practicum and Pre-Service Teachers' Self-Efficacy: Impact and Challenges

Author

Altarawneh, Awad Faek, Alkhazaleh, Mahmoud, Alkhazaleh, Ziad M., and Tarawneh, Rula Tahsin

Abstract

This study aimed to investigate the effect of school-based practicum experience on the self-efficacy of pre-service teachers (PTs) enrolled in Teacher Education Professional Diploma (TEPD) in Jordanian universities. The study followed mixed methods research. In the quantitative part, an online questionnaire was administered to 134 pre-service teachers (PTs) at the outset of the practicum program. Then it was readministered to the same sample after completing the practicum. In the qualitative part, semi-structured interviews were conducted after the practicum program to investigate the skills acquired by PTs during the school practicum and to identify the challenges, they faced during the school practicum experience. In the qualitative part, a total of 18 students voluntarily participated in the interviews. Results showed that the school-based practicum experience had a statistically significant effect on the overall mean scores of the PTs' self-efficacy in the pre-and post-applications and each study area (instructional strategies, classroom management, and student engagement). Furthermore, PTs reported several challenges during the school practicum, including the role of the academic supervisor, the cooperating school, the cooperating teacher, the nature of the TEPD program, and dealing with students.

Published
2023

25. Procedural Text Mining with Large Language Models

Author

Rula, Anisa and D'Souza, Jennifer

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Information Theory
Abstract

Recent advancements in the field of Natural Language Processing, particularly the development of large-scale language models that are pretrained on vast amounts of knowledge, are creating novel opportunities within the realm of Knowledge Engineering. In this paper, we investigate the usage of large language models (LLMs) in both zero-shot and in-context learning settings to tackle the problem of extracting procedures from unstructured PDF text in an incremental question-answering fashion. In particular, we leverage the current state-of-the-art GPT-4 (Generative Pre-trained Transformer 4) model, accompanied by two variations of in-context learning that involve an ontology with definitions of procedures and steps and a limited number of samples of few-shot learning. The findings highlight both the promise of this approach and the value of the in-context learning customisations. These modifications have the potential to significantly address the challenge of obtaining sufficient training data, a hurdle often encountered in deep learning-based Natural Language Processing techniques for procedure extraction., Comment: 8 pages, 4 figures, Accepted to The Twelfth International Conference on Knowledge Capture (K-Cap 2023)

Published
2023

26. A phytotherapeutic approach to hinder the resistance against clindamycin by MRSA: in vitro and in silico studies

Author

Amal Mayyas, Ali Al-Samydai, Nehaya Al-Karablieh, Waleed A Zalloum, Deniz Al-Tawalbeh, Farah Al-Mamoori, Rula A. Amr, Hamdi Al Nsairat, Simone Carradori, Lidia Kamal Al-Halaseh, and Talal Aburjai

Subjects
Antibiotic resistance, essential oils, MRSA, phytotherapy, quorum sensing, AgrA, Medicine, Medicine (General), R5-920
Abstract

Aims This study investigates the potential effects of essential oils (EOs) in enhancing the efficacy of clindamycin against Methicillin-resistant Staphylococcus aureus (MRSA) using in vitro and computer simulations. The research seeks to identify essential oils that exhibit synergistic activity with clindamycin and determine their potential key active components.Materials and Methods Essential oils commonly used in traditional medicine were tested for their antimicrobial activity against MRSA. The minimum inhibitory concentration (MIC) was determined using in vitro microdilution assays. A synergistic test with clindamycin was performed, and molecular docking studies evaluated the interaction between a key compound (trans-cinnamaldehyde) and MRSA protein.Results EOs from Cinnamomum verum, Rosmarinus officinalis, Salvia officinalis, and Thymus vulgaris demonstrated significant inhibitory and synergistic activities against MRSA, standard strain, and human clinical isolates. Gas Chromatography/Mass Spectroscopy identified trans-cinnamaldehyde, eucalyptol, and thymol as prominent antibacterial compounds. Molecular docking studies confirmed trans-cinnamaldehyde’s strong binding to MRSA’s AgrA protein, elucidating its enhanced efficacy.Conclusion The study underscores the potential of plant-based therapies to augment the effectiveness of conventional antibiotics like clindamycin in combating MRSA and addressing antibiotic resistance by integrating traditional plant remedies with modern medical approaches.

Published
2025
Full Text
View/download PDF

27. Discovery of Avian Paramyxoviruses APMV-1 and APMV-6 in Shorebirds and Waterfowl in Southern Ukraine.

Author

Klink, Amy, Rula, Oleksandr, Sushko, Mykola, Bezymennyi, Maksym, Mezinov, Oleksandr, Gaidash, Oleksandr, Bai, Xiao, Stegniy, Anton, Sapachova, Maryna, Datsenko, Roman, Skorokhod, Sergiy, Nedosekov, Vitalii, Hill, Nichola, Ninua, Levan, Kovalenko, Ganna, Ducluzeau, Anne, Mezhenskyi, Andriy, Buttler, Jeremy, Drown, Devin, Causey, Douglas, Stegniy, Borys, Gerilovych, Anton, Bortz, Eric, and Muzyka, Denys

Subjects
APMV, Azov-Black Sea region in Ukraine, minion, next-generation sequencing, surveillance of avian paramyxoviruses, viral ecology, wild birds, Animals, Newcastle disease virus, Ukraine, Phylogeny, Animals, Wild, Birds, Avulavirus
Abstract

Emerging RNA virus infections are a growing concern among domestic poultry industries due to the severe impact they can have on flock health and economic livelihoods. Avian paramyxoviruses (APMV; avulaviruses, AaV) are pathogenic, negative-sense RNA viruses that cause serious infections in the respiratory and central nervous systems. APMV was detected in multiple avian species during the 2017 wild bird migration season in Ukraine and studied using PCR, virus isolation, and sequencing. Of 4090 wild bird samples collected, mostly from southern Ukraine, eleven isolates were grown in ovo and identified for APMV serotype by hemagglutinin inhibition test as: APMV-1, APMV-4, APMV-6, and APMV-7. To build One Healths capacity to characterize APMV virulence and analyze the potential risks of spillover to immunologically naïve populations, we sequenced virus genomes in veterinary research labs in Ukraine using a nanopore (MinION) platform. RNA was extracted and amplified using a multiplex tiling primer approach to specifically capture full-length APMV-1 (n = 5) and APMV-6 (n = 2) genomes at high read depth. All APMV-1 and APMV-6 fusion (F) proteins possessed a monobasic cleavage site, suggesting these APMVs were likely low virulence, annually circulating strains. Utilization of this low-cost method will identify gaps in viral evolution and circulation in this understudied but important critical region for Eurasia.

Published
2023

31. Gender and Ocular Manifestations of Connective Tissue Diseases and Systemic Vasculitides

Author

Maria M. Choudhary, Rula A. Hajj-Ali, and Careen Y. Lowder

Subjects
Ophthalmology, RE1-994
Abstract

Ocular manifestations are present in many connective tissue diseases which are characterized by an immune system that is directed against self. In this paper, we review the ocular findings in various connective tissue diseases and systemic vasculitides and highlight gender differences in each disease. In rheumatoid arthritis, we find that dry eyes affect women nine times more than men. The other extra-articular manifestations of rheumatoid arthritis affect women three times more commonly than men. Systemic lupus erythematosus can involve all ocular structures and women are nine times more affected than men. Systemic sclerosis is a rare disease but, again, it is more common in women with a female to male ratio of 8 : 1. Polymyositis and dermatomyositis also affect women more commonly than men but no gender differences have been found in the incidence or disease course in the systemic vasculitides associated with antineutrophil cytoplasmic antibody such as granulomatosis with polyangiitis (GPA, formerly known as Wegener’s granulomatosis). Finally, Behcet’s disease is more common in males, and male gender is a risk factor for Behcet’s disease. There is a slight female preponderance in sarcoidosis with female gender carrying a worse prognosis in the outcome of ocular disease.

Published
2014
Full Text
View/download PDF

34. An optimized protocol for single cell transcriptional profiling by combinatorial indexing

Author

Martin, Beth K., Qiu, Chengxiang, Nichols, Eva, Phung, Melissa, Green-Gladden, Rula, Srivatsan, Sanjay, Blecher-Gonen, Ronnie, Beliveau, Brian J., Trapnell, Cole, Cao, Junyue, and Shendure, Jay

Subjects
Quantitative Biology - Genomics
Abstract

Single cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for recovering gene expression data from an exponentially scalable number of individual cells or nuclei. However, sci-RNA-seq is a complex protocol that has historically exhibited variable performance on different tissues, as well as lower sensitivity than alternative methods. Here we report a simplified, optimized version of the three-level sci-RNA-seq protocol that is faster, higher yield, more robust, and more sensitive, than the original sci-RNA-seq3 protocol, with reagent costs on the order of 1 cent per cell or less. We showcase the optimized protocol via whole organism analysis of an E16.5 mouse embryo, profiling ~380,000 nuclei in a single experiment. Finally, we introduce a "tiny sci-*" protocol for experiments where input is extremely limited., Comment: fixed a couple errors

Published
2021

35. Language Intensive Exposure in EFL Curriculum: Attitudes towards the Unlock Textbook Series at Birzeit University as a Case Study

Author

Qassrawi, Rania, Abuhussein, Haya Fayyad, Rafidi, Tina Jaber, and Yousef, Rula

Abstract

Language-intensive exposure and immersion can be regarded as key factors in developing proficient language learners. In the context of teaching English as a foreign language (EFL), the current research was conducted to compare two modes of teaching English using the "Unlock Textbook Series" published by Cambridge University Press at Birzeit University, Palestine. This research effort aimed at investigating the intensive and non-intensive students' attitudes towards the Unlock Textbook Series in addition to the effectiveness of the intensive and non-intensive modes of teaching based on EFL instructors' perspectives. In a descriptive design, two quantitative instruments were utilized to obtain data; a student questionnaire was implemented with students from the two tracks; intensive and non-intensive, whereas an attitudinal scale was used to examine the effectiveness of the two modes of teaching according to EFL instructors' perspectives. The participating students were (182) non-intensive and (100) intensive students. As for the instructors, fifteen (15) BZU instructors of English participated on the condition of teaching the two tracks. The findings revealed that there were statistically significant differences in the intensive and non-intensive students' attitudes towards the "Unlock Textbook Series" based on students' perspectives in favor of the intensive students. Additionally, it was shown that the intensive mode was more effective than the non-intensive based on instructors' perspectives. Accordingly, some recommendations were suggested.

Published
2023
Full Text
View/download PDF

39. An authentication model based on cryptography

Author

Obeidat, Ibrahim, Arjan, Ahmed AL, Amrat, Rula AL, and Ajmi, Rathaa AL

Subjects
Computer Science - Cryptography and Security, 68W01, F.2.2, I.2.7
Abstract

In this paper we proposed an authentication technique based on the user cards, to improve the authentication process in systems that allows remote access for the users, and raise the security rate during an exchange of their messages. in this technique the server performs two functions, the first function, register the users, and give him user ID, PIN code, and user private card contains secrecy information, which is used to encrypt user messages by using two kinds of encryption symmetric using RC4-Pr and asymmetric using RSA encryption., the second function, distribute the user's public card if the user demand that, in which the user sends the own authentication code with their own user ID and recipient user ID to the authentication check, and then the server sends the user public card to the recipient user, thus the sender user can send the messages to recipient user without back to the server again. We attained confidentiality using RC4-Pr and RSA encryption and message authentication, user signature, and mutual secret key by using RSA encryption. in this paper we also implement the proposal in [1] RC4-pr algorithm which is modified to improve the key weakness of basic RC4., Comment: 13 pages

Published
2021

45. COVID-19 in CXR: from Detection and Severity Scoring to Patient Disease Monitoring

Author

Amer, Rula, Frid-Adar, Maayan, Gozes, Ophir, Nassar, Jannette, and Greenspan, Hayit

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct a longitudinal study of disease progression. To achieve this goal, we developed a deep learning model for simultaneous detection and segmentation of pneumonia in chest Xray (CXR) images and generalized to COVID-19 pneumonia. The segmentations were utilized to calculate a "Pneumonia Ratio" which indicates the disease severity. The measurement of disease severity enables to build a disease extent profile over time for hospitalized patients. To validate the model relevance to the patient monitoring task, we developed a validation strategy which involves a synthesis of Digital Reconstructed Radiographs (DRRs - synthetic Xray) from serial CT scans; we then compared the disease progression profiles that were generated from the DRRs to those that were generated from CT volumes., Comment: paper was accepted to JBHI IEEE journal

Published
2020
Full Text
View/download PDF

46. Knowledge Graphs

Author

Hogan, Aidan, Blomqvist, Eva, Cochez, Michael, d'Amato, Claudia, de Melo, Gerard, Gutierrez, Claudio, Gayo, José Emilio Labra, Kirrane, Sabrina, Neumaier, Sebastian, Polleres, Axel, Navigli, Roberto, Ngomo, Axel-Cyrille Ngonga, Rashid, Sabbir M., Rula, Anisa, Schmelzeisen, Lukas, Sequeda, Juan, Staab, Steffen, and Zimmermann, Antoine

Subjects
Computer Science - Artificial Intelligence, Computer Science - Databases, Computer Science - Machine Learning
Abstract

In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models and query languages that are used for knowledge graphs. We discuss the roles of schema, identity, and context in knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We summarise methods for the creation, enrichment, quality assessment, refinement, and publication of knowledge graphs. We provide an overview of prominent open knowledge graphs and enterprise knowledge graphs, their applications, and how they use the aforementioned techniques. We conclude with high-level future research directions for knowledge graphs., Comment: Revision from v5: Correcting errata from previous version for entailment/models, and some other minor typos

Published
2020
Full Text
View/download PDF

49. Common myths and misconceptions about breast cancer causation among Palestinian women: a national cross-sectional study

Author

Elshami, Mohamedraed, Ismail, Islam Osama, Alser, Mohammed, Al-Slaibi, Ibrahim, Ghithan, Roba Jamal, Usrof, Faten Darwish, Qawasmi, Malak Ayman Mousa, Okshiya, Heba Mahmoud, Shurrab, Nouran Ramzi Shaban, Mahfouz, Ibtisam Ismail, Fannon, Aseel AbdulQader, Hawa, Mona Radi Mohammad, Giacaman, Narmeen, Ahmaro, Manar, Zaatreh, Rula Khader, AbuKhalil, Wafa Aqel, Melhim, Noor Khairi, Madbouh, Ruba Jamal, Hziema, Hala Jamal Abu, Lahlooh, Raghad Abed-Allateef, Ubaiat, Sara Nawaf, Jaffal, Nour Ali, Alawna, Reem Khaled, Abed, Salsabeel Naeem, Abuzahra, Bessan Nimer Ali, Kwaik, Aya Jawad Abu, Dodin, Mays Hafez, Taha, Raghad Othman, Alashqar, Dina Mohammed, Mobarak, Roaa Abd-al-Fattah, Smerat, Tasneem, Albarqi, Shurouq I., Abu-El-Noor, Nasser, and Bottcher, Bettina

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results