Artificial Intelligence Reads Facial Features to Detect Genetic Disorders… A Faculty Member at the Nineveh College of Medicine Co-Supervises and Participates in the Defense of a Master’s Thesis at the University of Nineveh
September 11, 2026 2026-09-11 18:49Artificial Intelligence Reads Facial Features to Detect Genetic Disorders… A Faculty Member at the Nineveh College of Medicine Co-Supervises and Participates in the Defense of a Master’s Thesis at the University of Nineveh
الذكاء الاصطناعي يقرأ ملامح الوجه للكشف عن الاضطرابات الوراثية… تدريسي في كلية طب نينوى يشترك في إشراف ومناقشة رسالة ماجستير بجامعة نينوى
Assistant Professor Dr. Ali Adel Sharif, a faculty member at the College of Medicine—University of Nineveh, participated as an advisor and a member of the thesis defense committee for a master’s thesis at the College of Electronics Engineering—University of Nineveh, for the researcher Zafar Darrar Saeed Al-Jawadi, as part of scientific cooperation and the promotion of interdisciplinary studies among the university’s faculties. The thesis was titled: AI-Based Approaches for Genetic Disorder Diagnosis Based on Facial Phenotype “AI-Based Approaches for the Diagnosis of Genetic Disorders Based on Facial Phenotype” The study addressed the development of an automated framework based on artificial intelligence techniques and the analysis of facial morphological characteristics, with the aim of supporting the early detection and classification of genetic disorders based on geometric measurements extracted from frontal facial images. The joint supervision by Assistant Professor Dr. Ali Adel Sharif and Assistant Professor Dr. Muhammad Abdul-Muttalib Muhammad from the College of Electronics Engineering exemplified the integration of medical expertise, engineering technologies, and artificial intelligence in addressing contemporary research topics with medical applications. This collaboration is part of the Faculty of Medicine at the University of Nineveh’s initiative to support interdisciplinary research and strengthen scientific cooperation among the university’s faculties, particularly in fields that utilize artificial intelligence to advance diagnosis and medical science.
