Students Research

Students Research


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A student research paper entitles:
High-Utility Machine Learning Prediction of Somatic Copy Number Alteration Subtypes in Lung Cancer in Never Smokers

was accepted at the 2025 American Society of Human Genetics​

​By analyzing data from over 230 patients, the team built AI models that can classify patients into three distinct groups, each with different risks and treatment possibilities, shedding light on the idea of predicting such subtypes using variables that can be measured without expensive techniques like whole-genome sequencing. The models became even more accurate when genetic information was added.

One key finding was that TP53 gene changes, along with tumor appearance and type, were especially useful in identifying more aggressive forms of the disease.

This work moves us closer to more personalized and precise care for lung cancer patients.

Authors:

Jehad Yasin, Abd-Alrahman Obeid, Faris Qtaishat, Muaath Alsufi, Osama Younis, Mohammad Ghanem, Zaid Muhanna

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Ongoing investigations are being conducted across several projects, engaging many research students

  1. Speech Evaluation and articulation Proficiency in Patients Post-Denture Placement
  2. Breast Cancer Diagnosis
  3. Wrist Index fracture analysis
  4. Speech Evaluation for post dental treatment
  5. The use of deep learning concept to identify the type of implants radiographically a multi-center study.
  6. Transferring Knowledge from MIMIC-CXR: A Deep Learning Pipeline for Real-World Chest XRay Diagnosis.
  7. AI-Assisted Ventilator Tuning During Surgery: A Real-Time Decision Support Model for Anesthesiologists
  8. Predicting Chromosomal Instability in Pancreatic Adenocarcinoma Using Histopathology, Genomics, and Clinical Information
  9. Investigating the Utility of AI for Mental Illness Diagnosis LLMs vs Human Doctors for Text-Based Medical Consultations: Insight into Turing Performance and Patient Psychology