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Michael Saban

Ph.D. Student

Michael Saban is a Ph.D. student in Computer Science at Loyola University Chicago working at the intersection of artificial intelligence and healthcare. His research applies machine learning, natural language processing, and large language models to clinical decision support, with a focus on emergency and critical care. His work includes clinical stroke prediction, multimodal modeling of electronic health record data, LLM-based clinical information extraction and summarization, and AI-driven prehospital stroke triage. He has published research in Scientific Reports and the Journal of Human Hypertension and has presented work at AMIA and the ClinicalNLP workshop at LREC. His technical work includes Python, R, PyTorch, large language models, NLP, multimodal machine learning, and clinical modeling.

Major

Education

  • Ph.D. in Computer Science, Loyola University Chicago — 2024–In Progress
  • M.S. in Bioinformatics, Loyola University Chicago — 2021–2023
  • B.S. in Biology, Loyola University Chicago — 2018–2022

Research Interests

Artificial Intelligence, Clinical AI, Natural Language Processing, Large Language Models, Machine Learning, Multimodal Machine Learning, Clinical Decision Support, Healthcare Informatics, Electronic Health Records, Stroke Prediction, Clinical NLP

Professional Employment

  • Graduate Research Assistant, Loyola University Chicago — 2024–Present
  • Research Assistant, Loyola University Chicago — 2023–2024