Gender Bias in Artificial Intelligence: Severity Prediction at an Early Stage of COVID-19.

ABSTRACT: Artificial intelligence (AI) technologies have been applied in various medical domains to predict patient outcomes with high accuracy. As AI becomes more widely adopted, the problem of model bias is increasingly apparent. In this study, we investigate the model bias that can occur when training a model using datasets for only one particular gender and aim to present new insights into the bias issue. For the investigation, we considered an AI model that predicts severity at an early stage based on the medical records of coronavirus disease (COVID-19) patients. For 5,601 confirmed COVID-19 patients, we used 37 medical records, namely, basic patient information, physical index, initial examination findings, clinical findings, comorbidity diseases, and general blood test results at an early st

SUBMITTER: Chung H 

PROVIDER: S-EPMC8667070 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature