The AI and Emerging Technologies in Medicine concentration is shaping the future of health care through advanced technology. Offered through the Icahn School of Medicine at Mount Sinai’s PhD in Biomedical Sciences program, this training area focuses on harnessing the power of AI and machine learning to transform biomedical research and improve patient outcomes.

Designed for students with strong quantitative skills, the program provides a robust foundation in AI and machine learning techniques as it applies to health care. Participants learn to develop sophisticated predictive models for diagnostics and therapeutics while drawing on knowledge from computer science, mathematics, and engineering. Through partnerships with leading technical institutions, this training also offers opportunities for collaborative research and professional growth, preparing students to become leaders in AI-informed medicine.

Our Master of Science in Biomedical Data Science and AI prepares students to address critical health care challenges through advanced data science and artificial intelligence technologies. The program develops professionals who can leverage large electronic medical record repositories, cutting-edge AI tools, and multidisciplinary coursework to transform biomedical data into actionable insights.

By applying data science and AI methodologies, graduates of the program are equipped to drive innovations in precision medicine, including personalized treatment strategies, advanced biomedical image analysis, and comprehensive improvements in health care delivery.

The Mount Sinai and Hasso Plattner Institute Student Exchange Program is available to selected Master of Science in Biomedical Data Science and AI (MDSAI) students throughout their time in the program. The Hasso Plattner Institute (HPI), affiliated with the University of Potsdam, is among Europe's leading centers for data science and digital engineering. Each year, a small cohort of up to four students participates: two Mount Sinai MDSAI students travel to HPI, and two HPI data science master's students travel to Mount Sinai. Students join a research lab at the host institution, working under a collaborating PI who remains connected to them at their home institution. This research aligns with each student's capstone project, offering a research-intensive experience at the intersection of biomedical data science, AI, and digital health.

The exchange program is fully funded for on-campus MDSAI students, with two tuition scholarships awarded annually, travel expenses covered, and living expenses subsidized. Eligible students must complete their first semester in the MDSAI program before applying. Internal applications open during the fall semester and are due in December, with selections announced in January. Selected students travel to HPI in early October of Year 2, timed to HPI's later semester start. Capstone research begins that same fall. Only two spots are awarded per institution each year, making this a competitive opportunity for students seeking international research collaboration with faculty at two leading institutions.

Advances in computing power, learning algorithms, big data, and other technologies have the potential to make the world a happier, healthier place. Mount Sinai would like to ensure that the most brilliant minds in machine learning can focus on the development of in artificial intelligence for human health.

The Windreich Department of Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai is the foremost department of its kind within a medical school. Our goal is to make the tools and techniques of AI available to all Mount Sinai researchers and physicians throughout the Health System’s hospitals and 400-plus ambulatory clinics.

To help build a world-class research program for AI- and data-driven innovation in human health, the department offers the Eric and Wendy Schmidt AI in Human Health Fellowship. Our aim is to embed talented early-career machine-learning scientists across our health system, focusing on clinically relevant questions. We aim to reduce health disparities in our communities, improve patient outcomes, and propel science forward to new frontiers. 

Throughout the duration of their tenure, all Eric and Wendy Schmidt AI in Human Health Fellows are expected to develop research programs, submit initial NIH grants, recognize Schmidt Sciences in research publications, and, ideally, become Assistant Professors within the Icahn School of Medicine upon the successful completion of their fellowship.

We welcome you to learn more and apply for the Eric and Wendy Schmidt AI in Human Health Fellowship.

The Mid-Career Instruction in Data and AI Skills Training Program (MIDAS) Training Program is a 4-week training course designed for learners at all levels seeking to build or expand their understanding of Artificial Intelligence and Machine Learning in healthcare. Whether you are new to AI/ML or looking to deepen your expertise, MIDAS offers structured, interactive learning that connects technical concepts to real-world clinical and research applications.

The program is jointly developed by the Department of Medicine (Division of D3M) and the Windreich Department of AI and Human Health. MIDAS is spearheaded by Dr. Neomi Shah, Dr. Girish Nadkarni, and Dr. Lili Chan.

There are two tiers of participation: 

Basic Offering (4 weeks, fewer sessions than Advanced)  — Foundational AI/ML concepts, applications, and best practices. Encouraged for learners looking to gain a broad overview of AI.

Advanced Offering (4 weeks, more sessions than Basic) — Includes Basic content plus labs, specialized applications, deployment strategies, and ethics. Encouraged for learners interested in more technical knowledge and learning how to code.

The MIDAS program is held once a year. Discounted rates are available for trainees and internal employees.

Register Here: https://mountsinai.formstack.com/forms/midas_registration

For more information as to whether MIDAS is a good fit for your needs, please refer to our FAQ below: 

Frequently Asked Questions

Is MIDAS the right course for me?
MIDAS is designed for clinicians, researchers, healthcare professionals, and learners who want a structured introduction to machine learning for clinical research. If you’re interested in understanding how AI models are built, evaluated, and applied in healthcare—and want enough foundational knowledge to effectively collaborate with technical teams—MIDAS is for you.

What topics does MIDAS cover?
The course provides a high-level introduction to key AI and machine learning concepts used in healthcare, including supervised learning, model evaluation, neural networks, transformers, natural language processing (NLP), and responsible AI. Through lectures and hands-on experience offered in the Advanced course, you’ll gain practical insight into how these methods are used in clinical research. 

Should I choose Basic or Advanced?
The central difference between our Basic and Advanced offering is the frequency of meetings and inclusion of learning about the laboratory sessions where you will learn basic coding. While learners choosing the Basic course may be looking to simply understand the concepts, Advanced learners are additionally learn basics of coding.

Will I learn how to build AI models from scratch?
No. MIDAS is not intended to make participants fully independent machine learning engineers. You will be shown and provided the code to train a model from scratch and learn the basic components of how to build a model. While it will give you basic knowledge, due to the length of our program we won’t provide enough foundation to build your own model.

Will there be hands-on learning?
Yes. In addition to lectures, the Advanced MIDAS offering includes interactive sessions where participants gain practical experience working with AI concepts and tools. The goal is to help bridge the gap between theory and real-world applications.

Do I need a background in computer science or programming?
No prior machine learning experience is required. The course is designed to make complex AI concepts accessible to healthcare professionals while still providing meaningful depth.

Is this course focused on medical imaging or genomics?
No. While examples may occasionally draw from different areas of medicine, MIDAS is not a specialized course in medical imaging, radiology AI, or genomics. The emphasis is on core machine learning concepts and their application to clinical research using healthcare data.

What will I be able to do after completing MIDAS?
After completing the course, you should be able to:

• Understand the fundamentals of modern machine learning and AI in healthcare.
• Critically evaluate AI research and recognize common strengths and limitations.
• Collaborate more effectively with data scientists and AI developers.
• Contribute to or supervise AI-enabled clinical research projects.
• Use large language models and other AI tools more thoughtfully by understanding the principles behind them.

What makes MIDAS different from other AI courses?
MIDAS emphasizes understanding rather than just using AI tools. Rather than focusing solely on prompting an LLM or running existing software, the course teaches the theory behind modern machine learning alongside practical applications, giving participants the knowledge to ask better questions, evaluate AI outputs, and make informed decisions in clinical research.

AIHH Grand Rounds is a monthly seminar series showcasing cutting-edge research at the intersection of AI, data science, and medicine. Each session features a keynote talk followed by open discussion to encourage interdisciplinary collaboration.

The series launched on September 15, 2025, and takes place both in person and virtually via Zoom. Speakers include both internal and external experts in AI and healthcare. For more details, please refer to our upcoming calendar of events. This series is accredited for CME and designed to foster learning and collaboration across the Mount Sinai Health System.

This four-hour class is designed for clinical staff and focuses on enhancing foundational knowledge of Artificial Intelligence in clinical practice. Offerings are held on a quarterly basis. Please check Peak to see if registration for our soonest offering is available.

For any questions, please contact duffy2@mssm.edu.