A pathologist-annotated dataset for validating artificial intelligence: A project description and pilot study

• Main Authors: Sarah N Dudgeon (Author), Si Wen (Author), Matthew G Hanna (Author), Rajarsi Gupta (Author), Mohamed Amgad (Author), Manasi Sheth (Author), Hetal Marble (Author), Richard Huang (Author), Markus D Herrmann (Author), Clifford H Szu (Author), Darick Tong (Author), Bruce Werness (Author), Evan Szu (Author), Denis Larsimont (Author), Anant Madabhushi (Author), Evangelos Hytopoulos (Author), Weijie Chen (Author), Rajendra Singh (Author), Steven N Hart (Author), Ashish Sharma (Author), Joel Saltz (Author), Roberto Salgado (Author), Brandon D Gallas (Author)
• Format: Book
• Published: Elsevier, 2021-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Purpose: Validating artificial intelligence algorithms for clinical use in medical images is a challenging endeavor due to a lack of standard reference data (ground truth). This topic typically occupies a small portion of the discussion in research papers since most of the efforts are focused on dev...