Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction

ObjectivesThe Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require scrutiny for potential biases. We address this over...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	BMJ health & care informatics Ročník 29; číslo 1; s. e100457
Hlavní autori:	Straw, Isabel, Wu, Honghan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England BMJ Publishing Group Ltd 01.04.2022 BMJ Publishing Group LTD BMJ Publishing Group
Predmet:	Algorithms Artificial Intelligence Bayes Theorem Bias Biomarkers BMJ Health Informatics Delivery of Health Care Female Gender differences Health Equity Health informatics Humans Liver Diseases Machine Learning Male Original Research Public health informatics Supervised Machine Learning United Kingdom > UK Public health informatics BMJ Health Informatics Health Equity Artificial intelligence Machine Learning
ISSN:	2632-1009, 2632-1009
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!