The Technion-Rambam Initiative in Medical AI, “TERA” was launched in March 2022 as a joint-initiative between The Technion and Rambam Health Care Campus – combining clinical expertise, basic science, and engineering in fighting human disease using large medical datasets and state-of-the-art advances in AI.
The mission of TERA is to initiate, support and promote academic research and educational activities between the two institutions and partners in the field of medical AI.
In the growing field of AI in medicine, the current situation is that solutions and insights developed in the lab usually do not enter the clinical practice. TERA aims to tackle this gap between research studies and the clinical implementation and health benefit that AI can provide.
Rambam collects medical data and biological samples as part of routine practice. Furthermore, clinical experts in Rambam come up with problems and challenges that, if solved, could significantly improve the care patients receive. The combination of health and biobank data with Rambam’s clinical knowledge is fertile ground for Technion scientists who can create and prospectively evaluate new algorithmic solutions to the most pressing medical challenges in diverse fields ranging from internal medicine to cardiology, cancer and intensive care to name a few.
TERA is uniquely poised to develop AI based solutions and rapidly translate them to a clinical-study in real-world settings aimed to assess their use and effectiveness in improving patient outcomes. Therefore, TERA aims to close the loop between medical data and biological sample availability and their actionable benefit to patient care. Research projects aim to improve clinical practices, quality of care, decisions on treatment strategies and medication selection, effectively implementing personalized medicine. We believe we are uniquely positioned to create a generator for innovation and discovery on the basis of the complementarity of Technion faculties and Rambam clinical expertise.
TERA includes a dedicated ecosystem and physical space integrated in Rambam. The physical space is the meeting point between researchers, clinician scientists, and graduate and MD/PhD students. It is staffed with dedicated professionals in the fields of data-science, IT, clinical trial methodologist, epidemiologist and statistician. TERA also addresses the ethical challenges in medical data sharing by providing the necessary ecosystem to work on the data “on site” or via secured cloud technology. Accordingly, TERA intention is to create an effective pipeline to properly collect, prepare, validate, document and share the large streams of medical data being generated in the dozens of medical units. TERA also support the regulatory and technical work needed to deploy pilot systems within Rambam units.
The monthly seminar provides a unique opportunity to listen to leading engineers and clinicians working in the field of medical data science. The guest talks will introduce to a wide audience the field of clinical data science, including those with both technical and non-technical backgrounds and provide a perspective on its future impact to the field of medicine. Register here to the TERA mailing list to stay tuned about future events.
Intelligent monitoring for the robust diagnosis of cardiovascular diseases using continuous long term ECG recordings.
People: Dr. Joachim A. Behar – Pr. Mahmoud Suleiman – Dr. Adi Elias – Shany Biton – Sheina Gendelman – Noam Ben Moshe.
Developing advanced tools to track and predict deterioration of critically-ill patients in the intensive care unit (surveillance and clinical decision support including treatment).
People: Dr. Danny Eytan – Dr. Ronit Almog – Dr. Joachim A. Behar – Dvir Cohen
Individual-level causal inference for prevention and optimal care of acutely decompensated heart failure patients developing acute kidney injury.
People: Dr. Oren Caspi – Dr. Uri Shalit – Pr. Doron Aronson – Rom Gutman
Fusing mechanistic and data-driven models for decision making in dynamic environments (real-time information on the patient’s cardiovascular status, expected trajectory and underlying disease processes).
People: Dr. Danny Eytan – Pr. Shie Mannor – Dr. Uri Shalit – Neta Ravid – Ori Linial
Establishing a predictive model for blood stream infections (BSI) during bone marrow transplantation (BMT).
People: Dr. Israel Henig – Dr. Asaf Miller – Oren Ploznik – Omer Shubi – Tom Yuviler – Tomer Karny
Developing advanced tools to track and predict birth weight.
People: Pr. Ron Beloosesky – Noam Keidar – Anastasiya Kuznetsova – Alon Hacohen – Galya Segal
The first round is closed. Stay tuned for the next round.
Asst. Professor, Faculty of Biomedical Engineering. Lab website
Linkedin
Director, Epidemiology Unit at Rambam.
Senior Data Scientist
Linkedin
Senior Software Developer
Linkedin
Asst. Professor, Pediatric Critical Care Unit at Rambam
Linkedin
Asst. Professor, Faculty of Data and Decision Science
Linkedin
Professor, Faculty of Electrical and Computer Engineering, Co-Director Tech.AI .
Linkedin
Director of Cardiology and Head Research Unit, Rambam Health Care Campus
Linkedin
Head of Rambam's Cardiovascular Research and Innovation Center.
Linkedin
Professor, Faculty of Medicine and Head of Technion Human Health Initiative.
Linkedin
Prof. at MIT, Harvard and clinician at Beth Israel Deaconess Medical Center.
Linkedin
For any questions, please contact us at: tera@technion.ac.il