Potential Applications of Machine Learning at Multidisciplinary Medical Team Meetings
November 03, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Bridget Kane, Jing Su, Saturnino Luz
arXiv ID
1911.00914
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY,
cs.HC,
cs.LG
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
While machine learning (ML) systems have produced great advances in several domains, their use in support of complex cooperative work remains a research challenge. A particularly challenging setting, and one that may benefit from ML support is the work of multidisciplinary medical teams (MDTs). This paper focuses on the activities performed during the multidisciplinary medical team meeting (MDTM), reviewing their main characteristics in light of a longitudinal analysis of several MDTs in a large teaching hospital over a period of ten years and of our development of ML methods to support MDTMs, and identifying opportunities and possible pitfalls for the use of ML to support MDTMs.
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