AI aiding medical decisions.
Noam Shomron, Professor & Principal Investigator Functional Genomics Laboratory, Tel Aviv University (10 min)
Identification of young adults at risk for type 2 diabetes
Gilad Twig, Head of population health research center, Gertner Institute of Epidemiology, Sheba Medical Center
To develop algorithms for the early detection of young adults at risk for type 2 diabetes and in particular, women with hyperglycemia in pregnancy. Avenues for collaborating may include working in parallel on a similar database elsewhere or assistance in AI performance.
New solutions for a sustainable future -Applied health technology @RISE
Sarah Thunberg, VP of the Business and Innovation Area Health and Life Science, Research Institutes of Sweden (RISE)
Amidst the evolving landscape of health challenges, crucial demands arise for technological advancements to push innovative approaches. Thus, health and wellbeing stand as a pivotal focus for RISE. Within this domain, our attention extends to encompass technical, digital, and pre-emptive solutions, all of which serve to bridge disparities and foster a sustainable, holistic state of health for all.
From Cells to Systems: Unravelling Patient Responses with Transcriptomics and Clinical Data
Dvir Aran, PhD, Assistant Professor, Faculty of Biology & Faculty of Computer Science, Technion - Israel Institute of Technology
My research focus is in two key areas: 1) Utilizing single-cell transcriptomics to decipher why some patients respond to immunotherapies while others don't, and 2) Applying causal inference and machine learning methodologies to electronic health records for improved patient care. I am seeking collaborators who have access to clinical data or clinical samples and could benefit from a partnership with a computational researcher to advance personalized medicine.
Leveraging tumor cell states for cancer treatment innovation
Michael Mints, Postdoc, Itay Tirosh lab, Department of Molecular Cell Biology, Weizmann Institute of Science/Cellyrix (10 min)
Tumour heterogeneity is often perceived as a negative trait, contributing to treatment failures, relapse, and metastasis. Intriguingly, recent breakthroughs have revealed highly recurring heterogeneity patterns among individuals, closely tied to clinical outcomes. We established a novel platform for bridging our understanding of tumour heterogeneity with clinical applications. We are seeking partnerships with early-stage investors, pharmaceutical and biotech companies, hospitals, and oncology researchers.
Integrating AI Solutions into clinical and administrative care processes
Erik Perjons, Associated Professor, Department of Computer and Systems Sciences, Stockholm University (10min)
Today, AI solutions are mostly supporting individual functions in healthcare. In order to transform healthcare in large, AI also needs to be better integrated into clinical and administrative care processes, including inter-organizational ones. Strategies, methods and best practices are needed for such a transformation. External competences: Business/Care Process Improvement using AI, Process Mining, Developing AI-capable care organizations, Interoperability and AI, AI Solution Engineering etc.
Closing the Loop: Technion-Rambam Initiative for Artificial Intelligence in Medicine - TERA
Joachim Behar, Director, Technion-Rambam Center for Artificial Intelligence in Healthcare (10 min)
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.