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Natalia Norori, Qiyang Hu, Florence Marcelle Aellen, Francesca Dalia Faraci, Athina Tzovara
Artificial intelligence (AI) has an astonishing potential in assisting clinical decision making and revolutionizing the field of health care. A major open challenge that AI will need to address before its integration in the clinical routine is that of algorithmic bias. Most AI algorithms need big datasets to learn from, but several groups of the human population have a long history of being absent or misrepresented in existing biomedical datasets. If the training data is misrepresentative of the population variability, AI is prone to reinforcing bias, which can lead to fatal outcomes, misdiagnoses, and lack of generalization. Here, we describe the challenges in rendering AI algorithms fairer, and we propose concrete steps for addressing bias using tools from the field of open science.
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Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021). Addressing bias in big data and AI for health care: A call for open science. Patterns, 2(10), 100347. https://doi.org/10.1016/j.patter.2021.100347
Norori, Natalia, et al. "Addressing bias in big data and AI for health care: A call for open science." Patterns, vol. 2, no. 10, 2021, pp. 100347, https://doi.org/10.1016/j.patter.2021.100347.
Norori, Natalia, Qiyang Hu, Florence Marcelle Aellen, Francesca Dalia Faraci, and Athina Tzovara. "Addressing bias in big data and AI for health care: A call for open science." Patterns 2, no. 10 (2021): 100347. https://doi.org/10.1016/j.patter.2021.100347.
Norori N., Hu Q., Aellen F. M. [и др.] Addressing bias in big data and AI for health care: A call for open science // Patterns. — 2021. — Vol. 2, № 10. — P. 100347. — URL: https://doi.org/10.1016/j.patter.2021.100347
@article{norori2021addressing,
title = {{Addressing bias in big data and AI for health care: A call for open science}},
author = {Natalia Norori and Qiyang Hu and Florence Marcelle Aellen and Francesca Dalia Faraci and Athina Tzovara},
journal = {Patterns},
year = {2021},
volume = {2},
number = {10},
pages = {100347},
doi = {10.1016/j.patter.2021.100347},
url = {https://doi.org/10.1016/j.patter.2021.100347}
}TY - JOUR AU - Norori, Natalia AU - Hu, Qiyang AU - Aellen, Florence Marcelle AU - Faraci, Francesca Dalia AU - Tzovara, Athina TI - Addressing bias in big data and AI for health care: A call for open science JO - Patterns VL - 2 IS - 10 SP - 100347 PY - 2021 DA - 2021/10/01 DO - 10.1016/j.patter.2021.100347 UR - https://doi.org/10.1016/j.patter.2021.100347 ER -
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