Publication: Machine Learning for Health: Algorithm Auditing & Quality Control
Machine Learning for Health: Algorithm Auditing & Quality Control
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Citations
Oala, L., Murchison, A. G., Balachandran, P., Choudhary, S., Fehr, J., et al, Meyer, M., Bielik, P., & Langer, N. (2021). Machine Learning for Health: Algorithm Auditing & Quality Control. Journal of Medical Systems, 45(12), 105. https://doi.org/10.1007/s10916-021-01783-y
Abstract
Abstract
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 t
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Creators (Authors)
- Oala, Luis
- Murchison, Andrew G
- Balachandran, Pradeep
- Choudhary, Shruti
- Fehr, Jana
- Meyer, Martin
- Bielik, Pavol
- Langer, Nicolas
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Citations
Oala, L., Murchison, A. G., Balachandran, P., Choudhary, S., Fehr, J., et al, Meyer, M., Bielik, P., & Langer, N. (2021). Machine Learning for Health: Algorithm Auditing & Quality Control. Journal of Medical Systems, 45(12), 105. https://doi.org/10.1007/s10916-021-01783-y
