A scientometric analysis of fairness in health AI literature.

• 主要な著者: Isabelle Rose I Alberto (著者), Nicole Rose I Alberto (著者), Yuksel Altinel (著者), Sarah Blacker (著者), William Warr Binotti (著者), Leo Anthony Celi (著者), Tiffany Chua (著者), Amelia Fiske (著者), Molly Griffin (著者), Gulce Karaca (著者), Nkiruka Mokolo (著者), David Kojo N Naawu (著者), Jonathan Patscheider (著者), Anton Petushkov (著者), Justin Michael Quion (著者), Charles Senteio (著者), Simon Taisbak (著者), İsmail Tırnova (著者), Harumi Tokashiki (著者), Adrian Velasquez (著者), Antonio Yaghy (著者), Keagan Yap (著者)
• フォーマット: 図書
• 出版事項: Public Library of Science (PLoS), 2024-01-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.

Artificial intelligence (AI) and machine learning are central components of today's medical environment. The fairness of AI, i.e. the ability of AI to be free from bias, has repeatedly come into question. This study investigates the diversity of members of academia whose scholarship poses quest...