著者

榊原 康文 伊藤 詩乃 田中 佑岳 佐藤 健吾 洪 繁 狩野 芳伸 Yasubumi Sakakibara Shino Ito Yugaku Tanaka Kengo Sato Shigeru Ko Yoshinobu Kano

雑誌

SIG-AIMED = SIG-AIMED

巻号頁・発行日

vol.001, 2015-09-29

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Toward a final goal to construct a medical diagnostic support system, as its pilot study, we attempt to build a question-answering program that automatically answers the medical licensing examination.

著者

岸本 泰士郎 吉村 道孝 北沢 桃子 榊原 康文 江口 洋子 藤田 卓仙 三村 將 Taishiro Kishimoto Michitaka Yoshimura Momoko Kitazawa Yasubumi Sakakibara Yoko Eguchi Takanori Fujita Masaru Mimura

雑誌

SIG-AIMED = SIG-AIMED

巻号頁・発行日

vol.001, 2015-09-29

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Most of the severity ratings are assessed through interview with patients in psychiatric filed. Such severity ratings sometimes lack objectivity that can lead to the delay/misjudgment of the treatment initiation/switch. A new technology which enables us to objectively quantify patients’ severity is needed. We here aim to develop a new device that analyzes patients’ facial expression, voice, and daily activities, and provides us with objective severity evaluation using machine learning technology. This study project was accepted by Japan Agency for Medical Research and Development (AMED) and will launch this year. The background of the study purpose and methods will be presented.