[HTML][HTML] The path toward equal performance in medical machine learning
To ensure equitable quality of care, differences in machine learning model performance
between patient groups must be addressed. Here, we argue that two separate mechanisms …
between patient groups must be addressed. Here, we argue that two separate mechanisms …
[HTML][HTML] AI recognition of patient race in medical imaging: a modelling study
Background Previous studies in medical imaging have shown disparate abilities of artificial
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
intelligence (AI) to detect a person's race, yet there is no known correlation for race on …
[HTML][HTML] Overcoming the challenges in the development and implementation of artificial intelligence in radiology: a comprehensive review of solutions beyond …
Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective
clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of …
clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of …
[HTML][HTML] Algorithmic encoding of protected characteristics in chest X-ray disease detection models
Background It has been rightfully emphasized that the use of AI for clinical decision making
could amplify health disparities. An algorithm may encode protected characteristics, and …
could amplify health disparities. An algorithm may encode protected characteristics, and …
Risk of bias in chest radiography deep learning foundation models
Purpose To analyze a recently published chest radiography foundation model for the
presence of biases that could lead to subgroup performance disparities across biologic sex …
presence of biases that could lead to subgroup performance disparities across biologic sex …
Demographic bias in misdiagnosis by computational pathology models
Despite increasing numbers of regulatory approvals, deep learning-based computational
pathology systems often overlook the impact of demographic factors on performance …
pathology systems often overlook the impact of demographic factors on performance …
Reading race: AI recognises patient's racial identity in medical images
Background: In medical imaging, prior studies have demonstrated disparate AI performance
by race, yet there is no known correlation for race on medical imaging that would be obvious …
by race, yet there is no known correlation for race on medical imaging that would be obvious …
Understanding and mitigating bias in imaging artificial intelligence
Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model
development, with potential for exacerbating health disparities. However, bias in imaging AI …
development, with potential for exacerbating health disparities. However, bias in imaging AI …
[HTML][HTML] Confounders mediate AI prediction of demographics in medical imaging
Deep learning has been shown to accurately assess “hidden” phenotypes from medical
imaging beyond traditional clinician interpretation. Using large echocardiography datasets …
imaging beyond traditional clinician interpretation. Using large echocardiography datasets …
[HTML][HTML] Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis
H Ieki, K Ito, M Saji, R Kawakami, Y Nagatomo… - Communications …, 2022 - nature.com
Background In recent years, there has been considerable research on the use of artificial
intelligence to estimate age and disease status from medical images. However, age …
intelligence to estimate age and disease status from medical images. However, age …