Deploying clinical machine learning? Consider the following...
- URL: http://arxiv.org/abs/2109.06919v3
- Date: Thu, 8 Jun 2023 15:53:37 GMT
- Title: Deploying clinical machine learning? Consider the following...
- Authors: Charles Lu, Ken Chang, Praveer Singh, Stuart Pomerantz, Sean Doyle,
Sujay Kakarmath, Christopher Bridge, Jayashree Kalpathy-Cramer
- Abstract summary: We believe a lack of appreciation for several considerations are a major cause for this discrepancy between expectation and reality.
We identify several main categories of challenges in order to better design and develop clinical machine learning applications.
- Score: 4.320268614534372
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Despite the intense attention and considerable investment into clinical
machine learning research, relatively few applications have been deployed at a
large-scale in a real-world clinical environment. While research is important
in advancing the state-of-the-art, translation is equally important in bringing
these techniques and technologies into a position to ultimately impact
healthcare. We believe a lack of appreciation for several considerations are a
major cause for this discrepancy between expectation and reality. To better
characterize a holistic perspective among researchers and practitioners, we
survey several practitioners with commercial experience in developing CML for
clinical deployment. Using these insights, we identify several main categories
of challenges in order to better design and develop clinical machine learning
applications.
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