News and Events

"Technion-Rambam Hack: Machine Learning in Healthcare" Conference Held at Rambam Health Care Campus

Publication Date: 3/9/2022 1:30 PM

The conference was the first event held by the newly established Technion-Rambam Center for Artificial Intelligence in Healthcare. MIT Professor Leo Anthony Celi addressed the conference on the topic of ensuring that machine learning for healthcare works for everyone.

The conference speakers and organizers (see text for details). 
Photography: Rambam HCCThe conference speakers and organizers (see text for details). Photography: Rambam HCC

In the photo (L-R):  Professor Lior Gepstein; Dr. Orna Berry, Director of Technology at the Google CTO’s Office; Professor Rafi Beyar; Dr. Joachim Behar; Professor Leo Anthony Celi; Dr. Ronit Almog, Rambam Health Care Campus; Professor Ran Balicer; Mr. Yoel Ben-Or, Head of Policy, Digital Health, Ministry of Health; Dr. Ruth Bergman, GE Healthcare; Dr. Danny Eytan, Rambam Health Care Campus.

Rambam Health Care Campus and the Technion – Israel Institute of Technology are setting up a new joint Technion-Rambam Center for Artificial Intelligence in Healthcare (CAIH) that will signal a revolution in medical decision-making. The CAIH, the first joint academic-hospital center in Israel and one of the first in the world, will develop advanced artificial intelligence systems to analyze a patient's condition. The center will focus on developing tools to help physicians select, in real time, the most appropriate and accurate medical treatment for a patient. These tools will be based on a complex and rapid analysis of all the relevant medical information that has accumulated in big medical databases over the years.

The center’s opening conference, which was held at Rambam on March 9, was attended by approximately 250 people, and featured leading researchers from Rambam, the Technion, the Massachusetts Institute of Technology (MIT), Israel’s Ministry of Health, Clalit Health Services, and companies such as GE and Roche. The opening remarks were delivered by Technion President Professor Uri Sivan, Rambam Director General Professor Michael Halberthal, Professor Shie Mannor, head of the Technion MLIS Center, and Professor Noam Ziv, who leads the THHI initiative. The first part of the conference dealt with current trends in machine learning in healthcare; the second part addressed access to medical databases in Israel; and the third part focused on the prospective evaluation of machine learning models in the clinical environment.

One of the most prominent speakers at the conference was one of the conference organizers, Professor Leo Anthony Celi, a senior researcher and Director of the MIT Laboratory of Computational Physiology (LCP), the organization behind SANA, which supports technological innovation for the benefit of all mankind, including developing countries. Professor Celi is a founder of MIMIC - a huge database serving more than 2,000 researchers in approximately 30 countries, creating a global community of medical researchers in the field of medical data science.

Other prominent speakers included Professor Ran Balicer, Chief Innovation Officer at Clalit Health Services, founding director of the Clalit Research Institute, a member of the Management Team for Epidemics at the Ministry of Health, and Head of the National COVID-19 Experts Advisory Team. Professor Rafi Beyar, Rambam’s former General Director, and one of the early visionaries at Rambam in establishing data science facilities also spoke at the conference.

The conference was organized by Dr. Danny Eytan, Dr. Ronit Almog, Professor Celi, and Dr. Joachim Behar.

About the Technion-Rambam Center for Artificial Intelligence in Healthcare

The Technion-Rambam Center for Artificial Intelligence in Healthcare is the brainchild of the two institutions and jointly funded by both. It will operate initially in the Meyer Building at Rambam and will later be transferred to the soon-to-be-completed Helmsley Health Discovery Tower on Rambam’s western campus. The center will initially run several flagship projects in the areas of cardiology, intensive care, and bone marrow transplants. In the second phase, the center will initiate and support new joint Rambam-Technion research projects. In the words of Dr. Joachim Behar of the Technion, the CAIH aim is to “create the leading Israeli academic center for medical AI committed to advanced medical and clinical research, resulting in significant and actionable benefit to patient care.”

According to Dr. Uri Shalit of the Technion, “The center will serve as a significant collaborative platform that will connect doctors and researchers from Rambam with scientists and engineers from the Technion, with the aim of promoting diagnosis and medical treatment through artificial intelligence. We, as data scientists, need above all a huge amount of data - Big Data - and the clinical world needs experts who will analyze this data and derive useful insights from it. For us as scientists, this is an important connection to the field and a significant means of influencing human well-being.”

A joint study by Dr. Oren Caspi, Director of the Heart Failure Unit at Rambam and a researcher at the Rappaport Faculty of Medicine at the Technion, and Technion Faculty of Medicine Professor Shai Shen-Orr, will form the basis of further research, in which patients with cardiac problems will be examined not only according to their chronological age but also according to their "immune age".

The development of these tools will involve doctors, researchers, and engineers from Rambam and the Technion who have harnessed the field of big data and computational learning to improve diagnosis and treatment. “This is the great innovation,” says Dr. Caspi, one of the leaders in establishing the center. “We all know the usual procedure – the patient is hospitalized, undergoes diagnostic tests and receives treatment to the best abilities of the medical staff. The new vision presented by the center is one of diagnosis and treatment based on extensive information from a huge number of patients. As a result, the doctor will be able to ‘tailor’ the patient’s treatment to be optimal, accurate and customized. The center's uniqueness will help us convert academic achievements in artificial intelligence and big data into therapeutic tools that are immediately available at the patient's bedside in the spirit of personalized medicine.”