Machine Learning in Medicine Symposium

Nov 21, 2019
|
All day
Event
Details

Advancing Medicine Through Machine Learning

Click here for more information and to register

Program Overview

Machine learning presents new opportunities to advance medical care and research. Far from a future promise, applications of machine learning tools are being used today, with more soon at hand. But are today’s researchers and medical professionals ready to harness these tools to their greatest impact? This symposium will present the current and near-future state of machine learning and discuss both the opportunities and challenges for its application in medicine. The symposium will feature numerous international experts and include a keynote address from Isaac Kohane MD PhD, the inaugural Chair of the Department of Biomedical Informatics at Harvard Medical School.

Learning Objectives

  • Identify the potential role of machine learning in medicine
  • Recognize the difference between machine learning, neural networks, and deep learning
  • Critically evaluate proposed new machine learning tools as it applies to imaging, pathology, pediatrics, brain science and mental health

Target Audience

  • Internal Medicine Specialists
  • Laboratory Medicine and Pathology Specialists
  • Medical Imaging Specialists
  • Psychiatry Specialists
  • Paediatrics Specialists
  • Medical Researcher/Scientists

Conference Co-Chairs

Rita Kandel MD FRCPC
Professor and Chair
Laboratory Medicine and Pathobiology
University of Toronto
Chief, Pathology and Laboratory Medicine
Mount Sinai Hospital

Kaveh Shojania MD FRCPC
Professor and Vice Chair
Department of Medicine
University of Toronto
Physician
Sunnybrook Hospital

Location
Peter Gilgan Centre for Research and Learning
686 Bay St
Toronto
M5G 0A4
2019-11-21 05:00:00 2019-11-21 05:00:00 UTC Machine Learning in Medicine Symposium Advancing Medicine Through Machine Learning Click here for more information and to register Program Overview Machine learning presents new opportunities to advance medical care and research. Far from a future promise, applications of machine learning tools are being used today, with more soon at hand. But are today’s researchers and medical professionals ready to harness these tools to their greatest impact? This symposium will present the current and near-future state of machine learning and discuss both the opportunities and challenges for its application in medicine. The symposium will feature numerous international experts and include a keynote address from Isaac Kohane MD PhD, the inaugural Chair of the Department of Biomedical Informatics at Harvard Medical School. Learning Objectives Identify the potential role of machine learning in medicine Recognize the difference between machine learning, neural networks, and deep learning Critically evaluate proposed new machine learning tools as it applies to imaging, pathology, pediatrics, brain science and mental health Target Audience Internal Medicine Specialists Laboratory Medicine and Pathology Specialists Medical Imaging Specialists Psychiatry Specialists Paediatrics Specialists Medical Researcher/Scientists Conference Co-Chairs Rita Kandel MD FRCPCProfessor and ChairLaboratory Medicine and PathobiologyUniversity of TorontoChief, Pathology and Laboratory MedicineMount Sinai Hospital Kaveh Shojania MD FRCPCProfessor and Vice ChairDepartment of MedicineUniversity of TorontoPhysicianSunnybrook Hospital 686 Bay St - Peter Gilgan Centre for Research and Learning discovery.commons@utoronto.ca