A smart, practical, deep learning-based clinical decision support tool for patients in the prostate-specific antigen gray zone: model development and validation.
Despite efforts to improve screening and early detection of prostate cancer (PC), no available biomarker has shown acceptable performance in patients with prostate-specific antigen (PSA) gray zones. We aimed to develop a deep learning-based prediction model with minimized parameters and missing value handling algorithms for PC and clinically significant PC (CSPC).
Author(s): Song, Sang Hun, Kim, Hwanik, Kim, Jung Kwon, Lee, Hakmin, Oh, Jong Jin, Lee, Sang-Chul, Jeong, Seong Jin, Hong, Sung Kyu, Lee, Junghoon, Yoo, Sangjun, Choo, Min-Soo, Cho, Min Chul, Son, Hwancheol, Jeong, Hyeon, Suh, Jungyo, Byun, Seok-Soo
DOI: 10.1093/jamia/ocac141