Prof. Cyrille Cohen – Level of neo-epitope predecessor and mutation type determine T cell activation of MHC binding peptides

Abstract Background Targeting epitopes derived from neo-antigens (or “neo-epitopes”) represents a promising immunotherapy approach with limited off-target effects. However, most peptides predicted using MHC binding prediction algorithms do not induce a CD8 + T cell response, and there is a crucial need to refine the predictions to readily identify the best antigens that could mediate T-cell responses. Such…

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Prof. Ron Unger – Machine learning for prediction of 30-day mortality after ST elevation myocardial infraction An Acute Coronary Syndrome Israeli Survey data mining study

Abstract Background Risk scores for prediction of mortality 30-days following a ST-segment elevation myocardial infarction (STEMI) have been developed using a conventional statistical approach. Objective To evaluate an array of machine learning (ML) algorithms for prediction of mortality at 30-days in STEMI patients and to compare these to the conventional validated risk scores. Methods This was a…

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