Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing.

Oala, L., Murchison, A., Balachandran, P., Choudhary, S., Fehr, J., Leite, A., et al. (2021). Machine Learning for Health: Algorithm Auditing & Quality Control. JOURNAL OF MEDICAL SYSTEMS, 45(12) [10.1007/s10916-021-01783-y].

Machine Learning for Health: Algorithm Auditing & Quality Control

Cabitza F.;
2021

Abstract

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing.
Articolo in rivista - Articolo scientifico
Algorithm; Artificial intelligence; Auditing; Health; Machine learning; Quality control;
English
2021
45
12
105
open
Oala, L., Murchison, A., Balachandran, P., Choudhary, S., Fehr, J., Leite, A., et al. (2021). Machine Learning for Health: Algorithm Auditing & Quality Control. JOURNAL OF MEDICAL SYSTEMS, 45(12) [10.1007/s10916-021-01783-y].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/399464
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