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2. ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based Approach

Author

Sadallah, Abdelrahman "Boda", Ahmed, Omar, Mohamed, Shimaa, Hatem, Omar, Hesham, Doaa, and Yousef, Ahmed H.

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

One of the main tasks of Natural Language Processing (NLP), is Named Entity Recognition (NER). It is used in many applications and also can be used as an intermediate step for other tasks. We present ANER, a web-based named entity recognizer for the Arabic, and Arabizi languages. The model is built upon BERT, which is a transformer-based encoder. It can recognize 50 different entity classes, covering various fields. We trained our model on the WikiFANE\_Gold dataset which consists of Wikipedia articles. We achieved an F1 score of 88.7\%, which beats CAMeL Tools' F1 score of 83\% on the ANERcorp dataset, which has only 4 classes. We also got an F1 score of 77.7\% on the NewsFANE\_Gold dataset which contains out-of-domain data from News articles. The system is deployed on a user-friendly web interface that accepts users' inputs in Arabic, or Arabizi. It allows users to explore the entities in the text by highlighting them. It can also direct users to get information about entities through Wikipedia directly. We added the ability to do NER using our model, or CAMeL Tools' model through our website. ANER is publicly accessible at \url{http://www.aner.online}. We also deployed our model on HuggingFace at https://huggingface.co/boda/ANER, to allow developers to test and use it.

Published
2023
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3. Prognostic value of laboratory markers in patients with acute pulmonary embolism

Author

Amany Omar Mohamed Omar, Yousef Ahmed Yousef Ahmed, Abd-Elazim Ahmed Abo Elfadl, Abeer Houssein Ali, Amal Abdallah Abdelrahman, and Khaled Mohamed Khaled Ali

Subjects
Pulmonary embolism (PE), Laboratory markers, Right ventricular dysfunction, Diseases of the respiratory system, RC705-779, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background Acute pulmonary embolism (APE) is a serious illness. Identifying prognostic factors for APE may help in the management of those patients. This study’s objective was to evaluate the prognostic value of laboratory markers in predicting right ventricular dysfunction (RVD) and 30-day mortality in pulmonary embolism patients. Methods Eighty patients with APE were enrolled and followed up for 30 days. Detailed echocardiography was done to evaluate RVD. All patients were subjected to arterial blood gas analysis, complete blood count (CBC), plasma concentration of C-reactive protein (CRP), serum D-dimer level, and serum troponin I level, and the following ratio were calculated: neutrophil-to-lymphocytic ratio (NLR), platelet to lymphocytic ratio (PLR), red cell distribution width (RDW), mean platelet volume (MPV), and alveolar to arterial gradient. Results Our results analysis revealed significantly elevated levels of median NLR, PLR, CRP, D-dimer, and troponin in both the RVD and non-survivor groups (P value

Published
2024
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8. Correction: Clinical and endoscopic characteristics of patients undergoing gastrointestinal endoscopic procedures in Egypt: a nationwide multicenter study

Author

Elbadry, Mohamed, El-Raey, Fathiya, Alboraie, Mohamed, Abdel-Samiee, Mohamed, Abdeltawab, Doaa, Ahmed, Mohammed Hussien, Sherief, Ahmed F, Eliwa, Ahmed, Tharwat, Mina, Abdelmawgod, Amira, Ahmed, Ossama Ashraf, Abdelsameea, Eman, Mahros, Aya, Moussa, Abdelmajeed M., Eid, Alshaimaa, Raafat, Khaled, Yousef, Ahmed, Rafea, Saad A. S., Alazzaq, Youssef, Mare’y, Mohamed, Abdelaziz, Ahmed, Ibrahim, El Sayed Abouzid, El Dayem, Waleed A. Abd, Abdelmoati, Ahmed A, Tawheed, Ahmed, Amer, Mohammad, Zaky, Samy, and El-Kassas, Mohamed

Published
2024
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10. Clinical and endoscopic characteristics of patients undergoing gastrointestinal endoscopic procedures in Egypt: a nationwide multicenter study

Author

Elbadry, Mohamed, El-Raey, Fathiya, Alboraie, Mohamed, Abdel-Samiee, Mohamed, Abdeltawab, Doaa, Ahmed, Mohammed Hussien, Sherief, Ahmed F, Eliwa, Ahmed, Tharwat, Mina, Abdelmawgod, Amira, Ahmed, Ossama Ashraf, Abdelsameea, Eman, Mahros, Aya, Moussa, Abdelmajeed M, Eid, Alshaimaa, Raafat, Khaled, Yousef, Ahmed, Rafea, Saad A. S., Alazzaq, Youssef, Mare’y, Mohamed, Abdelaziz, Ahmed, Ibrahim, El Sayed Abouzid, El Dayem, Waleed A Abd, Abdelmoati, Ahmed A, Tawheed, Ahmed, Amer, Mohammad, Zaky, Samy, and El-Kassas, Mohamed

Published
2024
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17. Generative Adversarial Networks for Artificial Satellite Image Creation and Manipulation

Author

Ghelichkhani, Samaneh, Salem, Yousef Ahmed Mohammed Al-Dhameri, Salahov, Huseyn, Adam, Feras Ashor Ibrik, Charbatji, Ahmad Jad, Abdulkareem, Marwa Issam, Jajodia, Sushil, Series Editor, Samarati, Pierangela, Series Editor, Lopez, Javier, Series Editor, Vaidya, Jaideep, Series Editor, Nowroozi, Ehsan, editor, Kallas, Kassem, editor, and Jolfaei, Alireza, editor

Published
2024
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28. Cognitive versus Behavioral Learning Analytics Dashboards for Supporting Learner's Awareness, Reflection, and Learning Process

Author

Yousef, Ahmed Mohamed Fahmy and Khatiry, Ahmed Ramadan

Abstract

Several governments across the world have temporarily closed educational institutions due to the COVID-19 pandemic. In response, numerous universities have seen a growing trend towards online learning scenarios. Thus, learning takes place not just within a person, but within and across the networks. However, the current implementations of open learning scenarios are facing many challenges, including: a) there is no systematic feature to track, evaluate and report the online learning activities of students; b) lack of immediacy and personal feedback; and c) lack of self-reflection. Consequently, Learning Analytics (LA) is one of the most distinguished solutions to address these challenges. In this study, the two kinds of LA dashboard, behavioral and cognitive, have been investigated. The methodological approach taken in this investigation was adopted from a design-based research framework, which blends empirical educational research with the theory-driven design of online learning environments. The initial sample consisted of 320 undergraduate nursing students. The cohort was divided into two groups according to the two types of LA dashboard. The findings have argued that behavioral dashboards took precedence over data evaluation items, while cognitive dashboards had the advantage in achieving the goals of LA -- e.g., awareness, self-reflection, and impact on learning process.

Published
2023
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43. Perceptions, attitude, and knowledge of Saudi parents towards the human papilloma virus vaccine

Author

Maqbul, Muazzam Sheriff, Allihaydan, Fatemah Saad, Elfaham, Rania Hisham, Baragaa, Lina Abdulaziz Ahmed, Elfaham, Shireen Hisham, Allihaydan, Nahlaa Saad, Alswat, Abdulrahman Khalid, Alhilal, Salam Omar, Alzaki, Reem Saleh, Jasim, Walaa Ebrahim Jaafar, Alduhailan, Yousef Ahmed, Alshehri, Abdullah Dhafer, Alshahrani, Saeed Ayidh, and Al Sumaih, Abdulrahman Musaed

Published
2024
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44. Knowledge and response of school teachers towards asthma exacerbation among school children in two arab countries

Author

Awadalla, Mohamed Fawzi M., Yousef, Ahmed, Ahmed Shiba, Hoda Ali, Humaed Almatani, Mohammad Uthman, Mohammad Ashshi, Mohammad Ahmad, Ibrahim Melibari, Anan Malik, Muhsin Alahmadi, Ahmed Abdulaziz, Mohammed Dhahwah, Abdulrahman Faisal, Ahmah Bukhari, Ahmad Mahmoud, Mubairik Alharbi, Raef Abdullah, Mohammed Juraybi, Ammar Mahdi, Ayidh Alraddadi, Abdulrahman Eid, and Babateen, Omar

Published
2024
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46. Small Bites, Big Impact: The Power of Nanolearning

Author

Yousef, Ahmed Mohamed Fahmy, Huang, Ronghuai, Tlili, Ahmed, Garcia, Manuel B., Mahmoud, Ayman Gabr, Metwally, Ahmed Hosny Saleh, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Anutariya, Chutiporn, editor, Liu, Dejian, editor, Tlili, Ahmed, editor, Yang, Junfeng, editor, and Chang, Maiga, editor

Published
2023
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47. Trans-Compiler-Based Database Code Conversion Model for Native Platforms and Languages

Author

Barakat, Rameez, Radwan, Moataz-Bellah A., Medhat, Walaa M., Yousef, Ahmed H., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fournier-Viger, Philippe, editor, Hassan, Ahmed, editor, and Bellatreche, Ladjel, editor

Published
2023
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48. A Deep Learning Approach for Quantifying Vocal Fold Dynamics during Connected Speech Using Laryngeal High-Speed Videoendoscopy

Author

Yousef, Ahmed M., Deliyski, Dimitar D., Zacharias, Stephanie R. C., de Alarcon, Alessandro, Orlikoff, Robert F., and Naghibolhosseini, Maryam

Abstract

Purpose: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details. Analysis of vocal fold vibration using HSV requires accurate segmentation of the vocal fold edges. This article presents an automated deep-learning scheme to segment the glottal area in HSV from which the glottal edges are derived during connected speech. Method: Using a custom-built HSV system, data were obtained from a vocally healthy participant reciting the "Rainbow Passage." A deep neural network was designed for glottal area segmentation in the HSV data. A recently introduced hybrid approach by the authors was utilized as an automated labeling tool to train the network on a set of HSV frames, where the glottis region was automatically annotated during vocal fold vibrations. The network was then tested against manually segmented frames using different metrics, intersection over union (IoU), and Boundary F1 (BF) score, and its performance was assessed on various phonatory events on the HSV sequence. Results: The designed network was successfully trained using the hybrid approach, without the need for manual labeling, and tested on the manually labeled data. The performance metrics showed a mean IoU of 0.82 and a mean BF score of 0.96. In addition, the evaluation assessment of the network's performance demonstrated an accurate segmentation of the glottal edges/area even during complex nonstationary phonatory events and when vocal folds were not vibrating, thus overcoming the limitations of the previous hybrid approach that could only be applied to the vibrating vocal folds. Conclusions: The introduced automated scheme guarantees accurate glottis representation in challenging color HSV data with lower image quality and excessive laryngeal maneuvers during all instances of connected speech. This facilitates the future development of HSV-based measures to assess the running vibratory characteristics of the vocal folds in speakers with and without voice disorder.

Published
2022
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