Sentiment Analysis of Dialectal Speech: Unveiling Emotions through Deep Learning Models by EZZELDIN, KHALED MOHAMED KHALED

“…A key contribution of this work is the development and evaluation of hybrid Deep Learning Models that combine CNN-BI-LSTM, CNN-GRU, GRU-CNN, GRU-BI-LSTM, and GRU-ANN architectures. …”
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Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…<h3>Background</h3><p dir="ltr">Existing BRCA2-specific variant pathogenicity prediction algorithms focus on the prediction of the functional impact of a subtype of variants alone. …”

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…Diverse dataset curation, bias mitigation strategies, continuous validation across populations, and collaborative efforts for regulatory approval are essential for the successful deployment of AI ECG in clinical settings and must be undertaken to address these issues. To guarantee a safe and successful deployment in clinical practice, the use of AI in cardiology must be done with a thorough understanding of the algorithms and their limits. …”

Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care by Barry Solaiman (19160614)

“…<p>This article proposes a framework for examining the ethical and legal concerns for using artificial intelligence (AI) in post-acute and long-term care (PA-LTC). …”

Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…In this study, I conduct a performance evaluation and comparison for various DL algorithms (LSTM, GRU, LSTM-ATT, CNN-BLSTM, CNN-LSTM, CNN-BILSTM-LSTM, and LSTM-TCN) on different datasets of Arabic cyberbullying to obtain more precise and dependable findings. …”
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Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions by Alaa Abd-alrazaq (17058018)

“…<p dir="ltr">The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on a wealth of professional and academic experience, we propose that LLMs hold promise for revolutionizing medical curriculum development, teaching methodologies, personalized study plans and learning materials, student assessments, and more. …”

Scatter search technique for exam timetabling by Mansour, Nashat

“…This approach is based on maintaining and evolving a population of solutions. We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. …”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”

Secrecy Performance of Decode-and-Forward Based Hybrid RF/VLC Relaying Systems by Jaber Al-Khori (16855470)

“…We develop physical layer security algorithms that mitigate eavesdropping on both RF and VLC networks based on zero-forcing beamforming techniques. …”

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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An Introduction to the Special Issue “Protein Glycation in Food, Nutrition, Health and Disease” by Naila Rabbani (291722)

“…In this editorial, we give a brief introduction to this Special Issue, the development of glycation research, the papers presented, and the declaration. …”

Prototype project management tool (PPMT) with cocomo calibration. (c1998) by Haddad, Ibrahim F.

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QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning by Md Nazmul Islam Shuzan (21842426)

“…<p dir="ltr">Patients with hyperglycemia require routine glucose monitoring to effectively treat their condition. We have developed a lightweight wristband device to capture Photoplethysmography (PPG) signals. …”

Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

“…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging by Maricar, Mohammed Farook

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An XML Document Comparison Framework by Tekli, Joe

“…Our approach consists of four main modules for i) discovering the structural commonalities between sub-trees, ii) identifying sub-tree semantic resemblances, iii) computing tree-based edit operations costs, iv) and computing tree edit distance. A prototype has been developed to evaluate the optimality and performance of our method. …”
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Virtualizing and Scheduling FPGA Resources in Cloud Computing Datacenters by Farhan, Abid

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Arabic Hotel Reviews Sentiment Analysis Using Deep Learning by ALMANSOORI, MOHAMMAD

“…Arabic Hotel Feedback sentiment analysis plays a significant role in understanding the opinions and sentiments expressed by customers in their reviews. …”
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WiMAX Models for the Smart Grid by Al-Omar, Ban Abdul Elah

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Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…</p><h2>Other Information</h2><p dir="ltr">Published in: Nursing Open<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1002/nop2.70195" target="_blank">https://dx.doi.org/10.1002/nop2.70195</a></p>…”