Deep learning‐based analysis of EGFR mutation prevalence in lung adenocarcinoma H&E whole slide images

• Main Authors: Jun Hyeong Park (Author), June Hyuck Lim (Author), Seonhwa Kim (Author), Chul‐Ho Kim (Author), Jeong‐Seok Choi (Author), Jun Hyeok Lim (Author), Lucia Kim (Author), Jae Won Chang (Author), Dongil Park (Author), Myung‐won Lee (Author), Sup Kim (Author), Il‐Seok Park (Author), Seung Hoon Han (Author), Eun Shin (Author), Jin Roh (Author), Jaesung Heo (Author)
• Format: Book
• Published: Wiley, 2024-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Abstract EGFR mutations are a major prognostic factor in lung adenocarcinoma. However, current detection methods require sufficient samples and are costly. Deep learning is promising for mutation prediction in histopathological image analysis but has limitations in that it does not sufficiently refl...