A Learning Program for Treatment Recommendations by Molecular Tumor Boards and Artificial Intelligence

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 b...

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Detalles Bibliográficos
Autores principales: Sunami, Kuniko, Naito, Yoichi, Saigusa, Yusuke, Amano, Toraji, Ennishi, Daisuke, Imai, Mitsuho, Kage, Hidenori, Kanai, Masashi, Kenmotsu, Hirotsugu, Komine, Keigo, Koyama, Takafumi, Maeda, Takahiro, Morita, Sachi, Sakai, Daisuke, Hirata, Makoto, Ito, Mamoru, Kozuki, Toshiyuki, Sakashita, Hiroyuki, Horinouchi, Hidehito, Okuma, Yusuke, Takashima, Atsuo, Kubo, Toshio, Hironaka, Shuichi, Segawa, Yoshihiko, Yakushijin, Yoshihiro, Bando, Hideaki, Makiyama, Akitaka, Suzuki, Tatsuya, Kinoshita, Ichiro, Kohsaka, Shinji, Ohe, Yuichiro, Ishioka, Chikashi, Yamamoto, Kouji, Tsuchihara, Katsuya, Yoshino, Takayuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2023
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690580/
https://www.ncbi.nlm.nih.gov/pubmed/38032680
http://dx.doi.org/10.1001/jamaoncol.2023.5120

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690580/
https://www.ncbi.nlm.nih.gov/pubmed/38032680
http://dx.doi.org/10.1001/jamaoncol.2023.5120

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