Machine Learning in Clinical Practice:  Using Commonly Available Lab Data for Early Identification of Potential Lower GI Pathology


January 9th, 2019 – 3 PM ET / 2 PM CT / 12 Noon PT

Machine Learning algorithms can find subtle signs of serious disease that are often missed by even the most astute clinicians. These powerful prediction tools can save lives through earlier detection, but only if they are operationalized effectively.  

In this webinar, Dr. William Manard, SLUCare CMIO, and Dr. Jeremy Orr, CMO of Medial EarlySign, will explain how a validated algorithm for the detection of occult bleeding related to lower GI disorders is being put into practice at SLUCare.  

The webinar will include a brief explanation of machine learning on clinical data, model performance characteristics, validation studies, technical and workflow considerations, and the challenges of clinical implementation of such models.
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Speakers: 
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William Manard, MD
Chief Medical Informatics Officer 
SLUCare Physician Group

Dr. William Manard serves as Chief Medical Informatics Officer for SLUCare Physician Group. He is an associate professor for the Department of Family Medicine at Saint Louis University School of Medicine and is faculty advisor for the Family Medicine Interest Group. 

His research interests include process and health system improvement, using decision support mechanisms to provide quality care, and utilizing interactive medical records to improve patient clinical outcomes.
Dr. Manard provides full-spectrum primary health care for people and families of all ages. He specializes in preventive/wellness care, chronic disease management and mental health, using the latest information technology to aid him in ensuring quality care for his patients



About the sponsor: Medial EarlySign

Medial EarlySign's solutions help our customers with their challenges of early detection and prevention of high-burden diseases. We provide insights based on post-analysis of existing, routine lab data and clinical records. This helps healthcare systems integrate these insights into their valued-base care workstreams to be able to provide patients with focused and personalized care.  Studies and in-system use demonstrate that our software identifies subtle, early clinical signs of illness and chronic conditions.
Jeremy Orr MD, MPH
Chief Medical Officer
Medial EarlySign

Jeremy has more than 20 years of clinical medical practice, population health, and healthcare IT experience. A practicing, board-certified family physician, Dr. Orr was named a “Top 100 Physician” during his time with Kaiser Permanente, and then went on to launch a medical practice that became part of Centura Health. While an Assistant Professor at the University of Colorado, he was selected as Teacher of the Year by residents. 
Prior to joining Medial, Jeremy served as the CMO of Boston based clinical data analytics firm Humedica (later Optum Analytics) and CMO of Los Angeles based clinical decision support company Stanson Health. Jeremy earned his MD at University at Buffalo and his MPH at Tulane. He is currently a PhD candidate at the University of Colorado School of Public Health focusing on data science and machine learning techniques applied to clinical data in epidemiology.