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Division of Health AIDivision of Health AI
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AboutTeamResearchPublicationsInternship
Division of Health AIDivision of Health AI

Clinical AI built with the data and clinicians of one of the largest health systems in the United States.

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Affiliations

  • Feinstein Institutes↗ (opens in new tab)
  • Northwell Health↗ (opens in new tab)
  • Zucker School of MedicineHofstra Northwell

Located at

  • Institute of Health System Science
  • Institute of Bioelectronic Medicine
  • Manhasset, New York

© 2026 Division of Health AI, Northwell Health. All rights reserved.

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Researcher · Division of Health AI

Theofilos Kanavos, MD

Theofilos Kanavos, MD, is an Elmezzi Scholar and physician researcher at the Division of Health AI at the Feinstein Institutes for Medical Research, Northwell Health. His research applies machine learning and deep learning to medical imaging and clinical data across oncology, ophthalmology, and sleep medicine. With the Zanos lab, he has co-authored systematic reviews on deep learning for interpreting lymphoma PET images and on AI-driven differentiation of uveal melanoma from nevus on fundus photographs, plus a machine learning study screening women for moderate-to-severe obstructive sleep apnea. He currently leads work on an LLM-powered framework for delirium annotation and early prediction from clinical and physiological data.

4 projects·3 papers

Theofilos Kanavos, MD
Role
Elmezzi Scholar
Google Scholar
Profile (opens in new tab)

Research projects

Research projects

ONSET

Delirium classification

Developing a machine learning framework to automatically identify delirium from clinical chart text using large language models, and building a predictive model to detect delirium onset early using clinical and physiological biomarkers.

Point-of-care AI

Archive · 3

  • Oncology and cancer imaging→
  • Ophthalmology and retinal imaging→
  • Sleep apnea (OSA)→

Publications

Selected papers

RespirationApr 2026

Bridging the Gender Gap in Obstructive Sleep Apnea: A Machine Learning Approach to Screening Women for Moderate-to-Severe Disease

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Translational Vision Science & TechnologyJan 2026

Artificial Intelligence-Driven Differentiation Between Uveal Melanoma and Nevus Based on Fundus Photographs: A Systematic Review and Meta-Analysis

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CancersDec 2024

A Systematic Review of the Applications of Deep Learning for the Interpretation of Positron Emission Tomography Images of Patients with Lymphoma

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Effrosyni Birbas, MD

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Derek Hansen, PhD

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Elly Konjkav, MS

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