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SUMMARY:Large-Scale Analytics and Machine Learning for Biomedical Data Types
DESCRIPTION:Wednesday June 28\, 2017 at 5:00 p.m. Dr. Shiva Amiri\, CEO of BioSymetrics Inc\, will be presenting “Large-Scale Analytics and Machine Learning for Biomedical Data Types”. \nDay & Time: Wednesday June 28\, 2017\n5:00 p.m. – 6:00 p.m. \nSpeaker: Dr. Shiva Amiri\nCEO of BioSymetrics Inc\nToronto\, Ontario\, Canada \nLocation: Room ENG288\nDepartment of Computer Science\nRyerson University\n245 Church St\, Toronto\, M5B 1Z4 \nContact: Alireza Sadeghian\, Alex Dela Cruz \nOrganizers: Signals & Computational Intelligence Chapter\, WIE \nAbstract: The scale of data being generated in medicine and research can easily overwhelm typical analytic capabilities. This is particularly true with MRI/fMRI scanning\, genomics data\, streaming/wearables data in addition to other clinical data types\, especially if in combination. \nChallenges include 1) large file sizes often in heterogeneous formats 2) currently no standard Protocol exists for extraction of standardized characteristics\, and 3) traditional methods for group-wise comparison can often result in spurious findings. \nThe talk will address these challenges by discussing customized processing pipelines built for multiple data types in biomedicine\, which enable effective machine learning and other types of analytics on these datasets. This approach leverages the rapid model building capabilities of our real-time machine learning software to iterate through normalization parameters for each data type and disease class. In addition\, this platform allows easy integration between the various medical data types (genome sequence\, phenotypic\, and metabolic data) allowing generation of more comprehensive disease classification models. \nThe ability to standardize and pre-process multiple types of biomedical data for machine learning\, no matter the source and type\, and effectively combine it with other data types is a powerful capability and holds promise for the future of diagnostics and precision medicine. \nBiography: Shiva Amiri is the CEO of BioSymetrics Inc. where they are developing a unique real-time machine learning technology for the analysis of massive data in biomedicine. BioSymetrics specializes in providing optimized pipelines for complex data types and effective methods in the analytics of integrated data. Prior to BioSymetrics she was the Chief Product Officer at Real Time Data Solutions Inc.\, she has led the Informatics and Analytics team at the Ontario Brain Institute\, where they developed Brain-CODE\, a large-scale neuroinformatics platform across the province of Ontario. She was previously the head of the British High Commission’s Science and Innovation team in Canada. Shiva completed her Ph.D. in Computational Biochemistry at the University of Oxford and her undergraduate degree in Computer Science and Human Biology at the University of Toronto. Shiva is involved with several organisations including Let’s Talk Science and Shabeh Jomeh International.
URL:https://www.ieeetoronto.ca/event/large-scale-analytics-and-machine-learning-for-biomedical-data-types/
LOCATION:Room ENG288\, 245 Church St\, Toronto\, M5B 1Z4
CATEGORIES:Signals & Computational Intelligence,Women in Engineering
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