Kuniko Sunami, Yoichi Naito, Yusuke Saigusa, Toraji Amano, Daisuke Ennishi, Mitsuho Imai, Hidenori Kage, Masashi Kanai, Hirotsugu Kenmotsu, Keigo Komine, Takafumi Koyama, Takahiro Maeda, Sachi Morita, Daisuke Sakai, Makoto Hirata, Mamoru Ito, Toshiyuki Kozuki, Hiroyuki Sakashita, Hidehito Horinouchi, Yusuke Okuma, Atsuo Takashima, Toshio Kubo, Shuichi Hironaka, Yoshihiko Segawa, Yoshihiro Yakushijin, Hideaki Bando, Akitaka Makiyama, Tatsuya Suzuki, Ichiro Kinoshita, Shinji Kohsaka, Yuichiro Ohe, Chikashi Ishioka, Kouji Yamamoto, Katsuya Tsuchihara, Takayuki Yoshino
IMPORTANCE: Substantial heterogeneity exists in treatment recommendations across molecular tumor boards (MTBs), especially for biomarkers with low evidence levels; therefore, the learning program is essential. OBJECTIVE: To determine whether a learning program sharing treatment recommendations for biomarkers with low evidence levels contributes to the standardization of MTBs and to investigate the efficacy of an artificial intelligence (AI)-based annotation system...
January 1, 2024: JAMA Oncology