What can a 2017 colonoscopy study teach us about using AI diagnostics safely in 2025? I explain this critical analogy and provide a full guide for physicians to evaluate AI tools in my latest presentation. Watch the full video:
www.youtube.com/watch?v=zmTK...

I’ve created three videos on AI-Assisted Medical Diagnostics, each focusing on a specific area:
Technical: www.youtube.com/watch?v=ycy7...
Clinical: www.youtube.com/watch?v=zmTK...
Practical: www.youtube.com/watch?v=HZ_z...

My babies in hard covers 🥰

My dog doesn’t like the book. He knows it’s the reason I wasn’t playing with him enough.

From our latest publication, "The objective of this study was not the maximization of predictive performance, but rather the demonstration of the essential role of clinical expertise in the development of reliable ML models for healthcare." DOI: 10.3390/surgeries6040087

Excited to share my new book: AI-Assisted Medical Diagnostics! It is a practical guide for clinicians; teaching you how to spot trustworthy AI/ML tools vs. hype in medical diagnostics. Learn to evaluate, integrate, and question AI solutions for safer, smarter patient care.

As demonstrated in our latest NYITCOM publication, we advocate that future ML-driven diagnostic studies adhere to the recent @fda.gov's recommended credibility assessment by analyzing training dynamics alongside traditional performance metrics. DOI: 10.3390/info16060432

Most ML studies lack external validation, raising concerns about the reliability of their reported performance. Our latest NYITCOM study demonstrates how without external testing, models do not perform as expected in real-world clinical settings. DOI: 10.3390/surgeries6010003

Our first article of 2025, "Impact of Convulsive Maternal Seizures on Fetus Dynamics", is out in the International Journal for Numerical Methods in Biomedical Engineering; Volume: 41, Issue: 1. DOI: 10.1002/cnm.3901. Explore our insights into maternal-fetal health at NYITCOM.

Doctors' diagnoses were correct 74% of the time without AI, 76% with AI assistance. If relied solely on AI, accuracy soared to 90%, demonstrating “doctors’ unwavering belief in a diagnosis they made, even when a chatbot suggests a better one.” (Not suggesting they should let AI make the diagnoses.)

They decorated everyone’s office door. Finding a workplace with a positive culture is essential for our well-being and productivity. A healthy environment promotes collaboration, creativity, and growth. Lucky me to have found such environment at NYITCOM. 🥰

Student and professor with their poster on Deep Learning Assessment of Knee Osteoarthritis presented at NYITCOM’s First Annual Biomedical Research, Innovation, and Imaging Center Research Retreat. I’m constantly impressed by our research students’ dedication, creativity, and passion for discovery.

Psychosis is a serious mental disorder characterized by a disconnection from reality.

Representing New York Tech’s College of Osteopathic Medicine at the 8th International Conference on Computational & Mathematical Biomedical Engineering (at George Mason University) with talk titled, “Biomechanical Effects of External Loading on Uterus Dynamics and Fetal Stress”.

Huge thanks to our New York Tech College of Osteopathic Medicine student Daniel Nasef for sharing our research on AI-driven classification of diabetic patients at the 15th Annual Machine Learning Symposium, hosted by the New York Academy of Sciences at the New York Academy of Medicine.

Our research paper, "Regressive Machine Learning for Real-Time Monitoring of Bed-Based Patients," has been published in Applied Sciences! It introduces an ML model that enhances real-time monitoring of bedridden patients. A special shout-out to the NYITCOM student co-authors!

Representing New York Tech’s College of Osteopathic Medicine at the 18th Long Island Systems, Applications and Technology Conference, with our paper, "Algorithm Selection and Data Utilization in Machine Learning for Medical Image Classification," copublished with student physician Mr. Gazi Hussain.