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Severe genetic diseases affect 7 million babies born every year worldwide. Currently, for an estimated 30% of patients with a presumed Mendelian disease, definitive diagnosis is possible by identification of the causative mutations after sequencing. Conversely, 70% of patients with suspected Mendelian disease do not receive a diagnosis immediately after available genetic testing methods are exhausted. However, approximately 250 novel gene-disease associations are identified every year. Reanalysis of exomes of patients with previously undiagnosable genetic conditions results in a significant fraction (4%-30%) of these cases becoming diagnosable in a period of 1 to 5 years after initial negative analysis. Millions such patients are predicted to be sequenced in the next five years. Nearly 70% of these will not obtain an immediate diagnosis. PubMed grows by over 1 million publications each year. Faced with this projected growth, how will 7,000 physicians and genetic counselors in the United States perform all the requisite analysis and reanalysis?
The talk will define a realized Artificial Intelligence framework for helping clinicians bring genetic diagnosis to all.


Gill Bejerano is an Associate Professor of Developmental Biology and Computer Science at Stanford University, and a member of the Stanford Artificial Intelligence (AI) Laboratory and Bio-X program. Mr. Bejerano is a pioneer of Human Genome research. He is the discoverer of "Ultraconserved Elements", human genomic regions that defy understanding of molecular evolution. He has also done influential work in applying Markovian models to biosequence analysis, and in showing that co-option of junk DNA into functional roles is an under-appreciated force shaping the evolution of the Human Genome. He serves Member of the Technical Advisory Board of Numenta, Inc. He holds a triple BSc in Mathematics, Physics and Computer Science (summa cum laude) and a PhD in Computer Science (Machine Learning applications in Bioinformatics) from the Hebrew University of Jerusalem.

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