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16 May

Temporomandibular Disorders Uncovered: A Multidisciplinary Journey from Diagnosis to Management

The Faculty of Dentistry at October University For Modern Sciences And Arts (MSA) is pleased to announce a specialized Scientific Day on Temporomandibular Disorders (TMDs), designed to provide an integrated, evidence-based understanding of TMDs through a multidisciplinary perspective combining orthodontics โ€ฆ

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MSA Computer Science Students Showcase Groundbreaking AI Research at ICTIS 2026 in Bangkok

MSA University proudly celebrates another remarkable achievement from the Faculty of Computer Science! ๐ŸŽ‰

The Faculty of Computer Science at October University for Modern Sciences and Arts (MSA) proudly congratulates our talented students Ahmed Mohamed Alansary and Molham Mohamed have successfully presented two of their graduation researches at the International Conference on Information and Communication Technology for Intelligent Systems (ICTIS 2026) held in Bangkok, Thailand.

Their research focuses on advancing Arabic medical text generation using large language models, with a strong emphasis on incorporating clinical severity into the training process. The researches were under the supervision of Dr. Ali Hamdi.

In their first paper, โ€œSeverity-Aware Weighted Loss for Arabic Medical Text Generation,โ€ they propose a novel loss function that dynamically adjusts learning based on the medical risk level of each case. By prioritizing clinically critical samples during training, the approach significantly improves model performance and ensures more reliable and risk-aware medical responses.

In their second paper, โ€œA Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation,โ€ they introduce a structured training strategy that gradually exposes models to medical cases from mild to critical severity. This curriculum-based approach enables models to learn foundational medical patterns before handling complex and high-risk scenarios, leading to consistent performance improvements across different architectures.

Together, these works highlight the importance of severity-aware learning in healthcare AI, demonstrating how training objectives and data organization strategies can directly impact the quality, reliability, and safety of generated medical content.

This achievement reflects the dedication and innovation of our students and highlights the growing contribution of MSA researchers to the global AI and healthcare technology community.

A heartfelt congratulations to Ahmed Mohamed Alansary, Molham Mohamed, and Dr. Ali Hamdi for this outstanding milestone. We wish them continued success in their academic and research journey!

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