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Comment
. 2021 Aug 30;193(34):E1351-E1357.
doi: 10.1503/cmaj.202434. Epub 2021 Aug 29.

Implementing machine learning in medicine

Amol A Verma  1 , Joshua Murray  2 , Russell Greiner  2 , Joseph Paul Cohen  2 , Kaveh G Shojania  2 , Marzyeh Ghassemi  2 , Sharon E Straus  2 , Chloe Pou-Prom  2 , Muhammad Mamdani  1
Affiliations
Comment

Implementing machine learning in medicine

Amol A Verma et al. CMAJ. .
No abstract available

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Conflict of interest statement

Competing interests: Amol Verma reports receiving a fellowship in Compassion and Artificial Intelligence from AMS Healthcare, in support of the present manuscript. Dr. Verma also reports receiving a Pathfinder Project grant from The Vector Institute (in support of the current work) and is a part-time employee of Ontario Health (which had no role in the work discussed in this paper). Amol Verma, Joshua Murray, Chloe Pou-Prom and Muhammad Mamdani led the development and implementation of the CHARTwatch early warning system at St. Michael’s Hospital, Toronto, Ontario, Canada. No other competing interests were declared.

Figures

Figure 1:
Figure 1:
A framework for the development and adoption of machine-learned solutions in clinical practice.
Figure 2:
Figure 2:
Team structure for each phase of development of an early warning system in the General Internal Medicine (GIM) service at St. Michael’s Hospital, Toronto, Ontario. Note: ICU = intensive care unit.
Figure 3:
Figure 3:
Clinical care pathway for patients in the General Internal Medicine (GIM) service with high predicted risk of clinical deterioration.
See this image and copyright information in PMC

Comment on

References

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