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1,502 results on '"Qasrawi A"'

5. A case of postgunshot deep femoral artery pseudo-aneurysm managed with coil embolization: A case report and literature review

Author

Hamza A. Abdul-Hafez, Ali Shakhshir, Laith Daraghmeh, Hala Qasrawi, Mohammed Khader, and Sultan Saada

Subjects
Pseudoaneurysm, Deep femoral artery, Gunshot injury, Trauma, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

In this case, the patient sustained a gunshot injury to the thigh and underwent surgery to treat a comminuted fracture. Six weeks after discharge, the patient presented with upper-thigh pain. Doppler ultrasound showed a deep femoral artery pseudoaneurysm, confirmed with computerized tomography (CT). We used coil embolization, a newly used method worldwide in recent years, to occlude the pseudoaneurysm. This reflects the complex, unknown mechanisms that contribute to such rare findings and draws attention to cases that require more extensive studies to understand potential pathological processes, leading to better management and improved outcomes. Furthermore, this case includes figures and images that illustrate the findings both pre- and postintervention, significantly enhancing the visual appeal of the procedure. Additionally, it provides a comprehensive review of other related cases, each with detailed presentations. Finally, this case illuminates the innovative application of embolization techniques in developing nations, which has resulted in lifesaving, cost-effectiveness, and a reduction in complications compared to other techniques.

Published
2025
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6. Double superior vena cava incidentally found during permanent catheter placement: A case report and literature review

Author

Ali Shakhshir, Hamza A. Abdul-Hafez, Muhammad Takhman, Hala Qasrawi, Mahdi Kittaneh, and Sultan Saada

Subjects
Persistent left superior vena cava, Double superior vena cava, Permanent catheter, Case report, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

A devastating admission to a tertiary hospital intensive care unit led to the discovery of a case of congenital duplicated superior vena cava (DSVC). Following the insertion of a temporary left internal jugular vein catheter, a subsequent chest X-ray indicated that the left catheter was not reaching the right heart. This resulted in a chest computed tomography scan with contrast, which confirmed the diagnosis of DSVC. The asymptomatic nature of these conditions reduces their prevalence. To date, there is no documented history of DSVC patients in Palestine. Therefore, it is important to report such a case to highlight the needs for larger studies in the future that aim to define the characteristics and varying features of patients with DSVC and the associated clinical findings.

Published
2025
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23. Enhanced Performance of Al/Nb2O5/Pt/Nb2O5/Ag Microwave Resonators Designed as Bandstop Filters and Negative Capacitance Sources

Author

Amjad Salamah Mohammad Aljaloud, Atef Fayez Qasrawi, and Latifah Hamad Khalid Alfhaid

Subjects
Nb2O5/Pt/Nb2O5, Microwave resonators, Return loss, Gigahertz, Negative capacitance, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Herein stacked layers of Nb2O5 coated onto Al substrates are fabricated as microwave resonators. Structural and morphological analyses on these stacked layers have shown the amorphous nature of growth of the stacked layers. Electrically, the resonators showed negative capacitance effect accompanied with series and parallel resonance at three well -distinguished notch frequencies. Additionally, the resonators exhibited bandstop filter characteristics with notch frequency ( f n) centered at 1.05 GHz, return loss ( R L) value of 9.0 dB and voltage standing wave ratios ( V S W R) of 2.12. To enhance the performance of the Nb2O5 microwave resonators, platinum nanosheets of thicknesses of 50 nm were inserted between layers of Nb2O5. Platinum nanosheets successfully decreased the surface roughness and increase the electrical conductivity by five orders of magnitude. Pt nanosheets additionally improved the values of f n, S 11, R L and V S W R to 1.16 GHz, 0.039, 30.3 dB and 1.12, respectively. The features of the microwave resonators comprising Pt nanosheets in its structure are promising for using them in communication technology.

Published
2024
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25. Multiplexed Dilute-and-Shoot Liquid Chromatography–Multiple-Reaction Monitoring Mass Spectrometry Clinical Assay for Metanephrines and Catecholamines in Human Urine

Author

Deema O. Qasrawi, Adriano M. C. Pimenta, Evgeniy V. Petrotchenko, Shaun Eintracht, and Christoph H. Borchers

Subjects
liquid chromatography–multiple-reaction monitoring mass spectrometry (LC-MRM-MS), metanephrines, catecholamines, adrenal gland, pheochromocytoma, urine, Microbiology, QR1-502
Abstract

Background: Quantifying urinary catecholamines and metanephrines is essential for the clinical screening and diagnosis of neuroendocrine tumours. HPLC with electrochemical detection (HPLC-ECD) is commonly used for this type of analysis but requires extensive sample cleanup. Simple and rapid dilute-and-shoot LC–multiple-reaction monitoring (MRM)-MS assays have been developed for quantitating these analytes in urine but have not yet been validated according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. Methods: A simple dilute-and-shoot sample preparation without derivatization was used. C18 RP-UPLC-MRM-MS and positive-ion ESI were used, usually with two transitions per analyte being monitored. Certified deuterated internal standards were used for each analyte. Results: This assay was validated according to the CLSI C62-A guidelines, including accuracy/trueness, imprecision, sensitivity, specificity, carryover, stability, and linearity. The final MRM-MS method was compared to the established HPLC-ECD clinical chemistry reference method. The run time was reduced from 25 min to 5 min. Conclusions: A simple, robust, rapid, and cost-effective LC-MRM-MS assay for measuring urinary catecholamines and metanephrines was developed and validated according to the CLSI guidelines. This validated method requires minimal sample manipulation before analysis and provides sensitivity, specificity, and improved precision. The implementation of this assay in clinical laboratories will facilitate early and accurate diagnosis.

Published
2025
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28. Microangiopathic Hemolytic Anemia as a Paraneoplastic Syndrome in a Patient with Metastatic Gastric Cancer

Author

Shahd T Natsheh, Tuqa Abu Ihlayel, Rawda Qasrawi, Qusai A Alsalah, Ahmad G Hammouri, Amer Zughayyer, and Hasan Arafat

Subjects
Medicine (General), R5-920
Abstract

Cancer-associated microangiopathic hemolytic anemia (CA-MAHA) is a rare paraneoplastic syndrome. The most effective approach to treating CA-MAHA is to address the underlying malignancy. Documented cases of CA-MAHA are limited to fewer than 50 patients in the literature. Herein, we present a 51-year-old female patient who developed CA-MAHA as a complication of gastric adenocarcinoma. Despite receiving neoadjuvant and adjuvant chemotherapy for gastric cancer, the patient experienced disease progression with metastatic lesions in the liver, pancreas, and other sites. This report highlights the challenges in diagnosing and distinguishing CA-MAHA from other similar conditions such as disseminated intravascular coagulation (DIC), hemolytic uremic syndrome (HUS), thrombotic thrombocytopenic purpura (TTP), and rheumatological paraneoplastic syndromes. Additionally, it concludes that CA-MAHA is associated with a poor prognosis and limited clinical benefit from treatment, emphasizing the need for early diagnosis and effective management strategies.

Published
2024
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29. The association between food preferences, eating behavior, and body weight among female university students in the United Arab Emirates

Author

Haleama Al Sabbah, Abir Ajab, Leila Cheikh Ismail, Ayesha Al Dhaheri, Sharifa Alblooshi, Siham Atari, Stephanny Vicuna Polo, Malak Amro, and Radwan Qasrawi

Subjects
obesity, food preferences, eating habits, lifestyle, fast food consumption patterns, Public aspects of medicine, RA1-1270
Abstract

IntroductionThis cross-sectional study investigated the associations between lifestyle, eating habits, food preferences, consumption patterns, and obesity among female university students in the United Arab Emirates (UAE).MethodsApproximately 4,728 participants, including both Emirati and Non-Emirati students (International Students). Data collection involved face-to-face interviews and anthropometric measurements, showing an interrelated relationship between food preferences and obesity among female university students.ResultsWhile sociodemographic factors and lifestyle habits contribute to obesity, this study uniquely focuses on the role of food preferences and food consumption patterns in body weight status. The findings reveal a significant correlation between the intake of high-sugar beverages–such as milk, juices, soft drinks, and energy drinks–and an increased risk of overweight and obesity among both Emirati and Non-Emirati populations. Notably, milk consumption was particularly associated with obesity in non-Emirati populations (F = 88.1, p

Published
2024
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32. The Higher and Lower-Order Thinking Skills (HOTS and LOTS) in Unlock English Textbooks (1st and 2nd Editions) Based on Bloom's Taxonomy: An Analysis Study

Author

Qasrawi, Rania and BeniAbdelrahman, Abdullah

Abstract

This study aims at analyzing "Unlock English Reading, Writing and Critical Thinking Skills" Textbooks (First and Second editions) in terms of the inclusion of the lower and the higher order thinking skills. The current study is a descriptive content analysis paper that followed a checklist containing the cognitive levels of Bloom's Taxonomy as well as a checklist of the possible verbs by OPAR (2012) that combined the Revised Taxonomy as well. The finding in this study indicated that majority of the cognitive objectives in the second edition belong to both LOTS (Comprehension) and HOTS (Analysis and Synthesis) whereas the focus of the first edition was mainly on Comprehension and Analysis. Some objectives, also, were paraphrased to reflect the cognitive objectives where they were more related to reading comprehension sub-skills (skimming, scanning, previewing, etc.). Based on the findings, some recommendations were listed.

Published
2020

35. Atraumatic splenic rupture after administering aspirin, clopidogrel, and heparin to a patient with unstable angina: A case report

Author

Iyad Maqboul, Laith Daraghmeh, Malak Raed Eleiwi, Hala Qasrawi, Maha Akkawi, and Ahmed AwadGhanem

Subjects
Medicine (General), R5-920
Abstract

It is a rare clinical phenomenon when a normal spleen ruptures spontaneously without any prior trauma. We present a 49-year-old male patient who was discovered to have a splenic rupture after he was referred to our facility as a case of unstable angina for cardiac catheterization based on nonspecific electrocardiogram ( ECG) abnormalities and symptoms of chest discomfort coupled with abdominal pain and shortness of breath. He received aspirin, clopidogrel, and heparin before arriving at our emergency department. A splenectomy was performed for the patient, and he recovered well. Despite the rarity of spontaneous splenic rupture, physicians must consider it while evaluating elderly patients who are experiencing abdominal pain while on anticoagulants. Splenic rupture should always be considered, and early diagnosis is essential for a better outcome.

Published
2024
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36. Extracellular vesicles in non-small cell lung cancer stemness and clinical applications

Author

Prita Pandya, Dania S. Al-Qasrawi, Skyeler Klinge, and Verline Justilien

Subjects
non-small cell lung cancer, cancer stem cells, extracellular vesicles, metastasis, tumor microenvironment, biomarkers, Immunologic diseases. Allergy, RC581-607
Abstract

Non-small cell lung carcinoma (NSCLC) accounts for 85% of lung cancers, the leading cause of cancer associated deaths in the US and worldwide. Within NSCLC tumors, there is a subpopulation of cancer cells termed cancer stem cells (CSCs) which exhibit stem-like properties that drive NSCLC progression, metastasis, relapse, and therapeutic resistance. Extracellular vesicles (EVs) are membrane-bound nanoparticles secreted by cells that carry vital messages for short- and long-range intercellular communication. Numerous studies have implicated NSCLC CSC-derived EVs in the factors associated with NSCLC lethality. In this review, we have discussed mechanisms of EV-directed cross-talk between CSCs and cells of the tumor microenvironment that promote stemness, tumor progression and metastasis in NSCLC. The mechanistic studies discussed herein have provided insights for developing novel NSCLC diagnostic and prognostic biomarkers and strategies to therapeutically target the NSCLC CSC niche.

Published
2024
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42. Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Author

Phelps, Nowell H, Singleton, Rosie K, Zhou, Bin, Heap, Rachel A, Mishra, Anu, Bennett, James E, Paciorek, Christopher J, Lhoste, Victor PF, Carrillo-Larco, Rodrigo M, Stevens, Gretchen A, Rodriguez-Martinez, Andrea, Bixby, Honor, Bentham, James, Di Cesare, Mariachiara, Danaei, Goodarz, Rayner, Archie W, Barradas-Pires, Ana, Cowan, Melanie J, Savin, Stefan, Riley, Leanne M, Aguilar-Salinas, Carlos A, Baker, Jennifer L, Barkat, Amina, Bhutta, Zulfiqar A, Branca, Francesco, Caixeta, Roberta B, Cuschieri, Sarah, Farzadfar, Farshad, Ganapathy, Shubash, Ikeda, Nayu, Iotova, Violeta, Kengne, Andre P, Khang, Young-Ho, Laxmaiah, Avula, Lin, Hsien-Ho, Ma, Jun, Mbanya, Jean Claude N, Miranda, J Jaime, Pradeepa, Rajendra, Rodríguez-Artalejo, Fernando, Sorić, Maroje, Turley, Maria, Wang, Limin, Webster-Kerr, Karen, Aarestrup, Julie, Abarca-Gómez, Leandra, Abbasi-Kangevari, Mohsen, Abdeen, Ziad A, Abdrakhmanova, Shynar, Abdul Ghaffar, Suhaila, Abdul Rahim, Hanan F, Abdurrahmonova, Zulfiya, Abu-Rmeileh, Niveen M, Abubakar Garba, Jamila, Acosta-Cazares, Benjamin, Adam, Ishag, Adamczyk, Marzena, Adams, Robert J, Adu-Afarwuah, Seth, Aekplakorn, Wichai, Afsana, Kaosar, Afzal, Shoaib, Agbor, Valirie N, Agdeppa, Imelda A, Aghazadeh-Attari, Javad, Ågren, Åsa, Aguenaou, Hassan, Agyemang, Charles, Ahmad, Mohamad Hasnan, Ahmad, Noor Ani, Ahmadi, Ali, Ahmadi, Naser, Ahmadi, Nastaran, Ahmed, Imran, Ahmed, Soheir H, Ahrens, Wolfgang, Aitmurzaeva, Gulmira, Ajlouni, Kamel, Al-Hazzaa, Hazzaa M, Al-Hinai, Halima, Al-Lahou, Badreya, Al-Lawati, Jawad A, Al-Raddadi, Rajaa, Al Asfoor, Deena, Al Hourani, Huda M, Al Qaoud, Nawal M, Alarouj, Monira, AlBuhairan, Fadia, AlDhukair, Shahla, Aldwairji, Maryam A, Alexius, Sylvia, Ali, Mohamed M, Alieva, Anna V, Alkandari, Abdullah, Alkerwi, Ala'a, Alkhatib, Buthaina M, Allin, Kristine, Alomary, Shaker A, Alomirah, Husam F, Alshangiti, Arwa M, Alvarez-Pedrerol, Mar, Aly, Eman, Amarapurkar, Deepak N, Amiano Etxezarreta, Pilar, Amoah, John, Amougou, Norbert, Amouyel, Philippe, Andersen, Lars Bo, Anderssen, Sigmund A, Androutsos, Odysseas, Ängquist, Lars, Anjana, Ranjit Mohan, Ansari-Moghaddam, Alireza, Anufrieva, Elena, Aounallah-Skhiri, Hajer, Araújo, Joana, Ariansen, Inger, Aris, Tahir, Arku, Raphael E, Arlappa, Nimmathota, Aryal, Krishna K, Assefa, Nega, Aspelund, Thor, Assah, Felix K, Assembekov, Batyrbek, Assunção, Maria Cecília F, Aung, May Soe, Aurélio de Valois, Correia Júnior Marco, Auvinen, Juha, Avdičová, Mária, Avi, Shina, Azad, Kishwar, Azevedo, Ana, Azimi-Nezhad, Mohsen, Azizi, Fereidoun, Babu, Bontha V, Bacopoulou, Flora, Bæksgaard Jørgensen, Maja, Baharudin, Azli, Bahijri, Suhad, Bajramovic, Izet, Bakacs, Marta, Balakrishna, Nagalla, Balanova, Yulia, Bamoshmoosh, Mohamed, Banach, Maciej, Banegas, José R, Baran, Joanna, Baran, Rafał, Barbagallo, Carlo M, Barbosa Filho, Valter, Barceló, Alberto, Baretić, Maja, Barnoya, Joaquin, Barrera, Lena, Barreto, Marta, Barros, Aluisio JD, Barros, Mauro Virgílio Gomes, Bartosiewicz, Anna, Basit, Abdul, Bastos, Joao Luiz, Bata, Iqbal, Batieha, Anwar M, Batista, Aline P, Batista, Rosangela L, Battakova, Zhamilya, Baur, Louise A, Bayauli, Pascal M, Beaglehole, Robert, Bel-Serrat, Silvia, Belavendra, Antonisamy, Ben Romdhane, Habiba, Benedek, Theodora, Benedics, Judith, Benet, Mikhail, Benitez Rolandi, Gilda Estela, Benzeval, Michaela, Bere, Elling, Berger, Nicolas, Bergh, Ingunn Holden, Berhane, Yemane, Berkinbayev, Salim, Bernabe-Ortiz, Antonio, Bernotiene, Gailute, Berrios Carrasola, Ximena, Bettiol, Heloísa, Beutel, Manfred E, Beybey, Augustin F, Bezerra, Jorge, Bhagyalaxmi, Aroor, Bharadwaj, Sumit, Bhargava, Santosh K, Bi, Hongsheng, Bi, Yufang, Bia, Daniel, Biasch, Katia, Bika Lele, Elysée Claude, Bikbov, Mukharram M, Bista, Bihungum, Bjelica, Dusko J, Bjerregaard, Anne A, Bjerregaard, Peter, Bjertness, Espen, Bjertness, Marius B, Björkelund, Cecilia, Bloch, Katia V, Blokstra, Anneke, Blychfeld Magnazu, Moran, Bo, Simona, Bobak, Martin, Boddy, Lynne M, Boehm, Bernhard O, Boer, Jolanda MA, Boggia, Jose G, Bogova, Elena, Boissonnet, Carlos P, Bojesen, Stig E, Bonaccio, Marialaura, Bongard, Vanina, Bonilla-Vargas, Alice, Bopp, Matthias, Borghs, Herman, Botomba, Steve, Bourne, Rupert RA, Bovet, Pascal, Boymatova, Khadichamo, Braeckevelt, Lien, Braeckman, Lutgart, Bragt, Marjolijn CE, Braithwaite, Tasanee, Brajkovich, Imperia, Breckenkamp, Juergen, Breda, João, Brenner, Hermann, Brewster, Lizzy M, Brian, Garry R, Briceño, Yajaira, Brinduse, Lacramioara, Bringolf-Isler, Bettina, Brito, Miguel, Brophy, Sinead, Brug, Johannes, Bruno, Graziella, Bugge, Anna, Buoncristiano, Marta, Burazeri, Genc, Burns, Con, Cabrera de León, Antonio, Cacciottolo, Joseph, Cai, Hui, Cama, Tilema, Cameron, Christine, Camolas, José, Can, Günay, Cândido, Ana Paula c, Cañete, Felicia, Capanzana, Mario V, Čapková, Naděžda, Capuano, Eduardo, Capuano, Rocco, Capuano, Vincenzo, Cardol, Marloes, Cardoso, Viviane C, Carlsson, Axel C, Carmuega, Esteban, Carvalho, Joana, Casajús, José A, Casanueva, Felipe F, Casas, Maribel, Celikcan, Ertugrul, Censi, Laura, Cervantes-Loaiza, Marvin, Cesar, Juraci A, Chamnan, Parinya, Chamukuttan, Snehalatha, Chan, Angelique, Chan, Queenie, Charchar, Fadi J, Charles, Marie-Aline, Chaturvedi, Himanshu K, Chaturvedi, Nish, Che Abdul Rahim, Norsyamlina, Chee, Miao Li, Chen, Chien-Jen, Chen, Fangfang, Chen, Huashuai, Chen, Long-Sheng, Chen, Shuohua, Chen, Zhengming, Cheng, Ching-Yu, Cheng, Yiling J, Cheraghian, Bahman, Chetrit, Angela, Chikova-Iscener, Ekaterina, Chinapaw, Mai JM, Chinnock, Anne, Chiolero, Arnaud, Chiou, Shu-Ti, Chirita-Emandi, Adela, Chirlaque, María-Dolores, Cho, Belong, Christensen, Kaare, Christofaro, Diego G, Chudek, Jerzy, Cifkova, Renata, Cilia, Michelle, Cinteza, Eliza, Cirillo, Massimo, Claessens, Frank, Clare, Philip, Clarke, Janine, Clays, Els, Cohen, Emmanuel, Cojocaru, Cosmin R, Colorado-Yohar, Sandra, Compañ-Gabucio, Laura-María, Concin, Hans, Confortin, Susana C, Cooper, Cyrus, Coppinger, Tara C, Corpeleijn, Eva, Cortés, Lilia Yadira, Costanzo, Simona, Cottel, Dominique, Cowell, Chris, Craig, Cora L, Crampin, Amelia C, Cross, Amanda J, Crujeiras, Ana B, Cruz, Juan J, Csányi, Tamás, Csilla, Semánová, Cucu, Alexandra M, Cui, Liufu, Cureau, Felipe V, Czenczek-Lewandowska, Ewelina, D'Arrigo, Graziella, d'Orsi, Eleonora, da Silva, Alanna G, Dacica, Liliana, Dahm, Christina C, Dallongeville, Jean, Damasceno, Albertino, Damsgaard, Camilla T, Dankner, Rachel, Dantoft, Thomas M, Dasgupta, Parasmani, Dastgiri, Saeed, Dauchet, Luc, Davletov, Kairat, de Assis Guedes de Vasconcelos, Francisco, de Assis, Maria Alice Altenburg, De Backer, Guy, De Bacquer, Dirk, De Bacquer, Jaco, de Bont, Jeroen, De Curtis, Amalia, de Fragas Hinnig, Patrícia, de Gaetano, Giovanni, De Henauw, Stefaan, De Miguel-Etayo, Pilar, De Neve, Jan-Walter, Duarte de Oliveira, Paula, De Ridder, David, De Ridder, Karin, de Rooij, Susanne R, de Sá, Ana Carolina MGN, De Smedt, Delphine, Deepa, Mohan, Deev, Alexander D, DeGennaro, Vincent Jr, Delisle, Hélène, Delpeuch, Francis, Demarest, Stefaan, Dennison, Elaine, Dereń, Katarzyna, Deschamps, Valérie, Devrishov, Ruslan D, Dhimal, Meghnath, Di Castelnuovo, Augusto, Dias-da-Costa, Juvenal Soares, Díaz-Sánchez, María Elena, Diaz, Alejandro, Díaz Fernández, Pedro, Díez Ripollés, María Pilar, Dika, Zivka, Djalalinia, Shirin, Djordjic, Visnja, Do, Ha TP, Dobson, Annette J, Dominguez, Liria, Donati, Maria Benedetta, Donfrancesco, Chiara, Dong, Guanghui, Dong, Yanhui, Donoso, Silvana P, Döring, Angela, Dorobantu, Maria, Dorosty, Ahmad Reza, Dörr, Marcus, Doua, Kouamelan, Dragano, Nico, Drygas, Wojciech, Du, Shufa, Duan, Jia Li, Duante, Charmaine A, Duboz, Priscilla, Duleva, Vesselka L, Dulskiene, Virginija, Dumith, Samuel C, Dushpanova, Anar, Dwyer, Terence, Dyussupova, Azhar, Dzerve, Vilnis, Dziankowska-Zaborszczyk, Elzbieta, Ebrahimi, Narges, Echeverría, Guadalupe, Eddie, Ricky, Eftekhar, Ebrahim, Efthymiou, Vasiliki, Egbagbe, Eruke E, Eggertsen, Robert, Eghtesad, Sareh, Eiben, Gabriele, Ekelund, Ulf, El-Khateeb, Mohammad, El Ammari, Laila, El Ati, Jalila, Eldemire-Shearer, Denise, Elliott, Paul, Enang, Ofem, Endevelt, Ronit, Engle-Stone, Reina, Erasmus, Rajiv T, Erem, Cihangir, Ergor, Gul, Eriksen, Louise, Eriksson, Johan G, Escobedo-de la Peña, Jorge, Eslami, Saeid, Esmaeili, Ali, Evans, Alun, Evans, Roger G, Faeh, David, Fagherazzi, Guy, Fakhradiyev, Ildar, Fakhretdinova, Albina A, Fall, Caroline H, Faramarzi, Elnaz, Farjam, Mojtaba, Farrugia Sant'Angelo, Victoria, Farzi, Yosef, Fattahi, Mohammad Reza, Fawwad, Asher, Fawzi, Wafaie W, Felix-Redondo, Francisco J, Ferguson, Trevor S, Fernandes, Romulo A, Fernández-Bergés, Daniel, Ferrante, Daniel, Ferrao, Thomas, Ferrari, Gerson, Ferrari, Marika, Ferrario, Marco M, Ferreccio, Catterina, Ferreira, Haroldo S, Ferrer, Eldridge, Ferrieres, Jean, Figueiró, Thamara Hubler, Fijalkowska, Anna, Fink, Günther, Fisberg, Mauro, Fischer, Krista, Foo, Leng Huat, Forsner, Maria, Fottrell, Edward F, Fouad, Heba M, Francis, Damian K, Franco, Maria do Carmo, Fras, Zlatko, Fraser, Brooklyn, Frontera, Guillermo, Fuchs, Flavio D, Fuchs, Sandra C, Fujiati, Isti I, Fujita, Yuki, Fumihiko, Matsuda, Furdela, Viktoriya, Furusawa, Takuro, Gabriela, Stefan Adela, Gaciong, Zbigniew, Gafencu, Mihai, Galán Cuesta, Manuel, Galbarczyk, Andrzej, Galcheva, Sonya V, Galenkamp, Henrike, Galeone, Daniela, Galfo, Myriam, Galvano, Fabio, Gao, Jingli, Gao, Pei, Garcia-de-la-Hera, Manoli, García Mérida, María José, García Solano, Marta, Gareta, Dickman, Garnett, Sarah P, Gaspoz, Jean-Michel, Gasull, Magda, Gaya, Adroaldo Cesar Araujo, Gaya, Anelise Reis, Gazzinelli, Andrea, Gehring, Ulrike, Geiger, Harald, Geleijnse, Johanna M, George, Ronnie, Gerdts, Eva, Ghaderi, Ebrahim, Ghamari, Seyyed-Hadi, Ghanbari, Ali, Ghasemi, Erfan, Gheorghe-Fronea, Oana-Florentina, Gialluisi, Alessandro, Giampaoli, Simona, Gianfagna, Francesco, Gieger, Christian, Gill, Tiffany K, Giovannelli, Jonathan, Gironella, Glen, Giwercman, Aleksander, Gkiouras, Konstantinos, Glushkova, Natalya, Godara, Ramesh, Godos, Justyna, Gogen, Sibel, Goldberg, Marcel, Goltzman, David, Gómez, Georgina, Gómez Gómez, Jesús Humberto, Gomez, Luis F, Gómez, Santiago F, Gomula, Aleksandra, Gonçalves Cordeiro da Silva, Bruna, Gonçalves, Helen, Gonçalves, Mauer, González-Alvarez, Ana D, Gonzalez-Chica, David A, González-Gil, Esther M, Gonzalez-Gross, Marcela, González-Leon, Margot, González-Rivas, Juan P, González-Villalpando, Clicerio, González-Villalpando, María-Elena, Gonzalez, Angel R, Gottrand, Frederic, Graça, Antonio Pedro, Grafnetter, Dušan, Grajda, Aneta, Grammatikopoulou, Maria G, Gregg, Edward W, Gregor, Ronald D, Gregório, Maria João, Grøholt, Else Karin, Grøntved, Anders, Grosso, Giuseppe, Gruden, Gabriella, Gu, Dongfeng, Guajardo, Viviana, Gualdi-Russo, Emanuela, Guallar-Castillón, Pilar, Gualtieri, Andrea, Gudmundsson, Elias F, Gudnason, Vilmundur, Guerchet, Maëlenn, Guerrero, Ramiro, Guessous, Idris, Guimaraes, Andre L, Gujral, Unjali P, Gulliford, Martin C, Gunnlaugsdottir, Johanna, Gunter, Marc J, Guo, Xiu-Hua, Guo, Yin, Gupta, Prakash C, Gupta, Rajeev, Gureje, Oye, Gurinović, Mirjana A, Gutiérrez González, Enrique, Gutierrez, Laura, Gutzwiller, Felix, Gwee, Xinyi, Ha, Seongjun, Hadaegh, Farzad, Hadjigeorgiou, Charalambos A, Haghshenas, Rosa, Hakimi, Hamid, Halkjær, Jytte, Hambleton, Ian R, Hamzeh, Behrooz, Hanekom, Willem A, Hange, Dominique, Hanif, Abu AM, Hantunen, Sari, Hao, Jie, Hardman, Carla Menêses, Hardy, Louise, Hari Kumar, Rachakulla, Harmer Lassen, Tina, Harooni, Javad, Hashemi-Shahri, Seyed Mohammad, Hassapidou, Maria, Hata, Jun, Haugsgjerd, Teresa, Hayes, Alison J, He, Jiang, He, Yuan, He, Yuna, Heidinger-Felső, Regina, Heier, Margit, Heinen, Mirjam, Hejgaard, Tatjana, Hendriks, Marleen Elisabeth, Henrique, Rafael dos Santos, Henriques, Ana, Hernandez Cadena, Leticia, Herrala, Sauli, Herrera-Cuenca, Marianella, Herrera, Victor M, Herter-Aeberli, Isabelle, 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Suárez-Medina, Ramón, Suarez-Ortegón, Milton F, Suebsamran, Phalakorn, Sugiyama, Mindy, Suka, Machi, Sulo, Gerhard, Sun, Chien-An, Sun, Liang, Sund, Malin, Sundström, Johan, Sung, Yn-Tz, Sunyer, Jordi, Suriyawongpaisal, Paibul, Sweis, Nabil William G, Swinburn, Boyd A, Sy, Rody G, Sylva, René Charles, Szponar, Lucjan, Tabone, Lorraine, Tai, E Shyong, Takuro, Furusawa, Tambalis, Konstantinos D, Tammesoo, Mari-Liis, Tamosiunas, Abdonas, Tan, Eng Joo, Tang, Xun, Tanrygulyyeva, Maya, Tanser, Frank, Tao, Yong, Tarawneh, Mohammed Rasoul, Tarp, Jakob, Tarqui-Mamani, Carolina B, Taxová Braunerová, Radka, Taylor, Anne, Taylor, Julie, Tchibindat, Félicité, Te Velde, Saskia, Tebar, William R, Tell, Grethe S, Tello, Tania, Tessema, Masresha, Tham, Yih Chung, Thankappan, KR, Theobald, Holger, Theodoridis, Xenophon, Thomas, Nihal, Thorand, Barbara, Thrift, Amanda G, Tichá, Ľubica, Timmermans, Erik J, Tjandrarini, Dwi Hapsari, Tjonneland, Anne, Tolonen, Hanna K, Tolstrup, Janne S, Tomaszewski, Maciej, Topbas, Murat, Topór-Mądry, Roman, Torheim, Liv Elin, Tornaritis, Michael J, Torrent, Maties, Torres-Collado, Laura, Toselli, Stefania, Touloumi, Giota, Traissac, Pierre, Tran, Thi Tuyet-Hanh, Tremblay, Mark S, Triantafyllou, Areti, Trichopoulos, Dimitrios, Trichopoulou, Antonia, Trinh, Oanh TH, Trivedi, Atul, Tshepo, Lechaba, Tsigga, Maria, Tsintavis, Panagiotis, Tsugane, Shoichiro, Tuitele, John, Tuliakova, Azaliia M, Tulloch-Reid, Marshall K, Tullu, Fikru, Tuomainen, Tomi-Pekka, Tuomilehto, Jaakko, Twig, Gilad, Tynelius, Per, Tzala, Evangelia, Tzotzas, Themistoklis, Tzourio, Christophe, Udoji, Nwannedimma, Ueda, Peter, Ugel, Eunice, Ukoli, Flora AM, Ulmer, Hanno, Unal, Belgin, Usupova, Zhamyila, Uusitalo, Hannu MT, Uysal, Nalan, Vaitkeviciute, Justina, Valdivia, Gonzalo, Vale, Susana, Valvi, Damaskini, van Dam, Rob M, van den Born, Bert-Jan, Van der Heyden, Johan, van der Schouw, Yvonne T, Van Herck, Koen, Van Lippevelde, Wendy, Van Minh, Hoang, Van Schoor, Natasja M, van Valkengoed, Irene GM, Vanderschueren, Dirk, Vanuzzo, Diego, Varbo, Anette, Varela-Moreiras, Gregorio, Vargas, Luz Nayibe, Varona-Pérez, Patricia, Vasan, Senthil K, Vasques, Daniel G, Vatasescu, Radu, Vega, Tomas, Veidebaum, Toomas, Velasquez-Melendez, Gustavo, Velika, Biruta, Verloigne, Maïté, Veronesi, Giovanni, Verschuren, WM Monique, Victora, Cesar G, Viegi, Giovanni, Viet, Lucie, Vik, Frøydis N, Vilar, Monica, Villalpando, Salvador, Vioque, Jesus, Viriyautsahakul, Napaphan, Virtanen, Jyrki K, Visser, Marjolein, Visvikis-Siest, Sophie, Viswanathan, Bharathi, Vladulescu, Mihaela, Vlasoff, Tiina, Vocanec, Dorja, Vollenweider, Peter, Völzke, Henry, Vourli, Georgia, Voutilainen, Ari, Vrijheid, Martine, Vrijkotte, Tanja GM, Vuletić, Silvije, Wade, Alisha N, Waldhör, Thomas, Walton, Janette, Wambiya, Elvis OA, Wan Bebakar, Wan Mohamad, Wan Mohamud, Wan Nazaimoon, Wanderley Júnior, Rildo de Souza, Wang, Chongjian, Wang, Huijun, Wang, Ming-Dong, Wang, Ningli, Wang, Qian, Wang, Xiangjun, Wang, Ya Xing, Wang, Ying-Wei, Wannamethee, S Goya, Wareham, Nicholas, Wartha, Olivia, Weber, Adelheid, Wedderkopp, Niels, Weghuber, Daniel, Wei, Wenbin, Weres, Aneta, Werner, Bo, Westbury, Leo D, Whincup, Peter H, Wichstrøm, Lars, Wickramasinghe, Kremlin, Widhalm, Kurt, Widyahening, Indah S, Więcek, Andrzej, Wild, Philipp S, Wilks, Rainford J, Willeit, Johann, Willeit, Peter, Williams, Julianne, Wilsgaard, Tom, Wirth, James P, Wojtyniak, Bogdan, Woldeyohannes, Meseret, Wolf, Kathrin, Wong-McClure, Roy A, Wong, Andrew, Wong, Emily B, Wong, Jyh Eiin, Wong, Tien Yin, Woo, Jean, Woodward, Mark, Wu, Frederick C, Wu, Hon-Yen, Wu, Jianfeng, Wu, Li Juan, Wu, Shouling, Wyszyńska, Justyna, Xu, Haiquan, Xu, Liang, Yaacob, Nor Azwany, Yamborisut, Uruwan, Yan, Li, Yan, Weili, Yang, Ling, Yang, Xiaoguang, Yang, Yang, Yardim, Nazan, Yasuharu, Tabara, Yépez García, Martha, Yiallouros, Panayiotis K, Yngve, Agneta, Yoosefi, Moein, Yoshihara, Akihiro, Yotov, Yoto, You, Qi Sheng, You, San-Lin, Younger-Coleman, Novie O, Yu, Yu-Ling, Yu, Yunjiang, Yusof, Safiah Md, Yusoff, Ahmad Faudzi, Zaccagni, Luciana, Zafiropulos, Vassilis, Zainuddin, Ahmad A, Zakavi, Seyed Rasoul, Zamani, Farhad, Zambon, Sabina, Zampelas, Antonis, Zamrazilová, Hana, Zapata, Maria Elisa, Zargar, Abdul Hamid, Zaw, Ko Ko, Zayed, Ayman A, Zdrojewski, Tomasz, Żegleń, Magdalena, Zejglicova, Kristyna, Zeljkovic Vrkic, Tajana, Zeng, Yi, Zentai, Andrea, Zhang, Bing, Zhang, Luxia, Zhang, Zhen-Yu, Zhao, Dong, Zhao, Ming-Hui, Zhao, Wenhua, Zhecheva, Yanitsa V, Zhen, Shiqi, Zheng, Wei, Zheng, Yingfeng, Zholdin, Bekbolat, Zhou, Maigeng, Zhu, Dan, Zimmet, Paul, Zins, Marie, Zitt, Emanuel, Zocalo, Yanina, Zoghlami, Nada, Zuñiga Cisneros, Julio, Zuziak, Monika, and Ezzati, Majid

Published
2024
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45. Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic

Author

Radwan Qasrawi, Maha Hoteit, Reema Tayyem, Khlood Bookari, Haleama Al Sabbah, Iman Kamel, Somaia Dashti, Sabika Allehdan, Hiba Bawadi, Mostafa Waly, Mohammed O. Ibrahim, The Regional CORONA COOKING Survey Group, Stephanny Vicuna Polo, and Diala Abu Al-Halawa

Subjects
Food insecurity, COVID-19, Food consumption score, Machine learning, Prediction, Arab countries, Public aspects of medicine, RA1-1270
Abstract

Abstract Background A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to predict food insecurity across ten Arab countries in the Gulf and Mediterranean regions. A total of 13,443 participants were extracted from the international Corona Cooking Survey conducted by 38 different countries during the COVID -19 pandemic. Results The findings indicate that Jordanian, Palestinian, Lebanese, and Saudi Arabian respondents reported the highest rates of food insecurity in the region (15.4%, 13.7%, 13.7% and 11.3% respectively). On the other hand, Oman and Bahrain reported the lowest rates (5.4% and 5.5% respectively). Our model obtained accuracy levels of 70%-82% in all algorithms. Gradient Boosting and Random Forest techniques had the highest performance levels in predicting food insecurity (82% and 80% respectively). Place of residence, age, financial instability, difficulties in accessing food, and depression were found to be the most relevant features associated with food insecurity. Conclusions The ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally.

Published
2023
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47. Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years

Author

Radwan Qasrawi, Sabri Sgahir, Maysaa Nemer, Mousa Halaikah, Manal Badrasawi, Malak Amro, Stephanny Vicuna Polo, Diala Abu Al-Halawa, Doa’a Mujahed, Lara Nasreddine, Ibrahim Elmadfa, Siham Atari, and Ayoub Al-Jawaldeh

Subjects
food insecurity, malnutrition, wasting, stunting, machine learning, public health, Pediatrics, RJ1-570
Abstract

Background: Food insecurity significantly impacts children’s health, affecting their development across cognitive, physical, and socio-emotional dimensions. This study explores the impact of food insecurity among children aged 6 months to 5 years, focusing on nutrient intake and its relationship with various forms of malnutrition. Methods: Utilizing machine learning algorithms, this study analyzed data from 819 children in the West Bank to investigate sociodemographic and health factors associated with food insecurity and its effects on nutritional status. The average age of the children was 33 months, with 52% boys and 48% girls. Results: The analysis revealed that 18.1% of children faced food insecurity, with household education, family income, locality, district, and age emerging as significant determinants. Children from food-insecure environments exhibited lower average weight, height, and mid-upper arm circumference compared to their food-secure counterparts, indicating a direct correlation between food insecurity and reduced nutritional and growth metrics. Moreover, the machine learning models observed vitamin B1 as a key indicator of all forms of malnutrition, alongside vitamin K1, vitamin A, and zinc. Specific nutrients like choline in the “underweight” category and carbohydrates in the “wasting” category were identified as unique nutritional priorities. Conclusion: This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking.

Published
2024
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48. Hybrid Ensemble Deep Learning Model for Advancing Ischemic Brain Stroke Detection and Classification in Clinical Application

Author

Radwan Qasrawi, Ibrahem Qdaih, Omar Daraghmeh, Suliman Thwib, Stephanny Vicuna Polo, Siham Atari, and Diala Abu Al-Halawa

Subjects
brain stroke, clinical application, deep learning, hybrid model, image enhancement, images, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95
Abstract

Ischemic brain strokes are severe medical conditions that occur due to blockages in the brain’s blood flow, often caused by blood clots or artery blockages. Early detection is crucial for effective treatment. This study aims to improve the detection and classification of ischemic brain strokes in clinical settings by introducing a new approach that integrates the stroke precision enhancement, ensemble deep learning, and intelligent lesion detection and segmentation models. The proposed hybrid model was trained and tested using a dataset of 10,000 computed tomography scans. A 25-fold cross-validation technique was employed, while the model’s performance was evaluated using accuracy, precision, recall, and F1 score. The findings indicate significant improvements in accuracy for different stages of stroke images when enhanced using the SPEM model with contrast-limited adaptive histogram equalization set to 4. Specifically, accuracy showed significant improvement (from 0.876 to 0.933) for hyper-acute stroke images; from 0.881 to 0.948 for acute stroke images, from 0.927 to 0.974 for sub-acute stroke images, and from 0.928 to 0.982 for chronic stroke images. Thus, the study shows significant promise for the detection and classification of ischemic brain strokes. Further research is needed to validate its performance on larger datasets and enhance its integration into clinical settings.

Published
2024
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49. Exploring AI governance in the Middle East and North Africa (MENA) region: gaps, efforts, and initiatives

Author

Hana Trigui, Fatma Guerfali, Emna Harigua-Souiai, Radwan Qasrawi, Chiraz Atri, Elie Salem Sokhn, Christo El Morr, Karima Hammami, Oussama Souiai, Jianhong Wu, Jude Dzevela Kong, Jean Jacques Rousseau, and Sadri Znaidi

Subjects
Artificial Intelligence (AI), AI readiness, AI governance, Regulatory framework, MENA Region, Information technology, T58.5-58.64, Political institutions and public administration (General), JF20-2112
Abstract

This commentary explores MENA”s AI governance, addressing gaps, showcasing successful strategies, and comparing national approaches. It emphasizes current deficiencies, highlights regional contributions to global AI governance, and offers insights into effective frameworks. The study reveals distinctions and trends in MENA”s national AI strategies, serving as a concise resource for policymakers and industry stakeholders.

Published
2024
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