Considerations in the reliability and fairness audits of predictive models for advance care planning

• Main Authors: Jonathan Lu (Author), Amelia Sattler (Author), Samantha Wang (Author), Ali Raza Khaki (Author), Alison Callahan (Author), Scott Fleming (Author), Rebecca Fong (Author), Benjamin Ehlert (Author), Ron C. Li (Author), Lisa Shieh (Author), Kavitha Ramchandran (Author), Michael F. Gensheimer (Author), Sarah Chobot (Author), Stephen Pfohl (Author), Siyun Li (Author), Kenny Shum (Author), Nitin Parikh (Author), Priya Desai (Author), Briththa Seevaratnam (Author), Melanie Hanson (Author), Margaret Smith (Author), Yizhe Xu (Author), Arjun Gokhale (Author), Steven Lin (Author), Michael A. Pfeffer (Author), Winifred Teuteberg (Author), Nigam H. Shah (Author)
• Format: Book
• Published: Frontiers Media S.A., 2022-09-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Multiple reporting guidelines for artificial intelligence (AI) models in healthcare recommend that models be audited for reliability and fairness. However, there is a gap of operational guidance for performing reliability and fairness audits in practice. Following guideline recommendations, we condu...