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Machine Learning for Healthcare and Life Sciences

IBM Research - Haifa

Clinical Genomic Analysis


Different technological breakthroughs over the last decades have led to the availability of unprecedented amounts of 'omic' data. With the sequencing costs going down rapidly, the vision of whole human genome sequencing below 1000$ is becoming a reality.

Together with the already vast amounts of genomic data published, it is a big data challenge to analyze all the expected genomic information both for sake of new research as well as for treatment recommendations at the point of care.

Since the birth of these new technologies it was recognized that machine learning and statistical techniques are essential in revealing useful insights out of these massive complex data. Since 2006, our group is consistently involved in this line of study. Thus, as part of the EuResist project we led the development of a novel Clinical Decision Support system for HIV patients, which analyzes clinical data along with corresponding viral genomic data of thousands of patients. We were also involved in the Hypergenes project, which focused on revealing the genetic basis of essential hypertension.

In recent years the team has a special focus on Oncology. We have developed the decision support system CliG, and we take part in the recently announced collaboration with the New York Genome Center to advance genomic medicine.

In the past 5 years, we have organized and hosted a yearly workshop devoted to clinical genomic analysis that attracts many participants from Israel, EMEA, and the US.

Our team is also leading the development of various analysis tools that will be integrated into a generic Clinical Decision Support system, as part of the cli-G grand-challenge project that was recently launched at HRL.

Contact: Yaara Goldschmidt