Books - KISHIMOTO Taishiro

耳鼻咽喉科ニューフロンティア―近未来医療を手にする (プラクティス耳鼻咽喉科の臨床)

木下翔太郎, 岸本泰士郎, 中山書店, 2025.06

精神医学の未来を担う新アカデミア-実装へのラストワンマイル-. 医良戦略2040 PARTⅡ

岸本泰士郎, 株式会社ロギカ書房, 2025

ミレニアム精神医学事典

三村將, 村松太郎, 内田裕之, 遠藤拓郎, 岸本泰士郎　他, 弘文堂, 2025

熱意を理性でドライブせよ

千葉大学医学部附属病院次世代医療構想センター, 吉村 健佑, 松本 晴樹, 近藤 克則 , 野口 晴子 , 小谷 和彦, 松本 俊彦 , 石井 洋介, 小笠原 定久, 山口 育子 , 鋪野 紀好, 津野 香奈美, 近藤 尚己, 川上 英良, 稲葉 可奈子, 岸本 泰士郎, 加藤 浩晃, 佐々木 淳 , ロギカ書房, 2025

自由会話のAI解析による認知症検知システムの開発. 認知症の予防・診断・介護DX

豊柴博義, 岸本泰士郎, エヌ・ティー・エス, 2024,  Page： 153-159

生体センシング技術の開発とヘルスケア、遠隔診断への応用

木下翔太郎, 古川渉太, 岸本泰士郎, 技術情報協会, 2024

精神医学領域におけるAI技術の活用. 先進医療NAVIGATOR 医療とAI最前線

岸本泰士郎, 木下翔太郎, 日本医学出版, 2022,  Page： 34-36

パート２第２章 安定・維持期の統合失調症治療, 統合失調症薬物治療ガイドライン2022

岸本泰士郎 他, 医学書院, 2022,  Page： 44-56

特攻性注射剤 (LAI). 統合失調症治療の新たなストラテジー　第二版

三澤史斉, 岸本泰士郎　他, 先端医学社, 2021.03,  Page： 67-71

Information technology and electronic health record to improve behavioral health services

Hilty D., Naslund J.A., Ahuja S., Torous J., Kishimoto T., Crawford A., Mental Health in a Digital World, 2021.01

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We continue to increase our exchange of information through health technologies, used to access, disseminate, and analyze information. Clinical informatics is a rapidly expanding area and facilitates patient-centered care as defined by quality, affordability, and timely health care. This chapter covers developments in information systems, electronic health records, electronic communications with patients and staff (e.g., alerts, texts), behavioral health indicators and related digital advances to improve practice and research. The reader can learn how to set goals toward quality outcomes and be efficient while remaining patient-centered using technology, and adapt to technological components and processes used by systems. By grasping how systems are designed and tailored to collect data, clinicians can use technology to inform decisions and facilitate outcomes. Setting priorities involves input from all care participants, as well as technological competencies for the clinician and institutional/organizational. Patient, clinician, and institutional competencies for skills, attitudes, and behaviors can align clinical care, training, and research missions and stimulate quality improvement.

• Access to Document (DOI)

精神科領域におけるオンライン診療. 必見！オンライン診療の実践と解説

木下翔太郎, 岸本泰士郎, 日本医事新報社, 2021,  Page： 139-147

うつ病. 今日の治療指針 2020年版電子版 付録 オンライン診療の手引き

岸本泰士郎, 医学書院, 2020.01

Autism Spectrum Disorder’s Severity Prediction Model Using Utterance Features for Automatic Diagnosis Support

Sakishita M., Ogawa C., Tsuchiya K.J., Iwabuchi T., Kishimoto T., Kano Y., Studies in Computational Intelligence, 2020

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Diagnoses of autism spectrum disorder (ASD) are difficult due to difference of interviewers and environments, etc. We show relations between utterance features and ASD severity scores, which were manually given by clinical psychologists. These scores are based on the Autism Diagnostic Observation Schedule (ADOS), which is the standard metrics for symptom evaluation for subjects who are suspected as ASD. We built our original corpus where we transcribed voice records of our ADOS evaluation experiment movies. Our corpus is the world largest as speech/dialog of ASD subjects, and there has been no such ADOS corpus available in Japanese language as far as we know. We investigated relationships between ADOS scores (severity) and our utterance features, automatically estimated their scores using support vector regression (SVR). Our average estimation errors were around error rates that human ADOS experts are required not to exceed. Because our detailed analysis for each part of the ADOS test (“puzzle toy assembly + story telling” part and the “depiction of a picture” part) shows different error rates, effectiveness of our features would depend on the contents of the records. Our entire results suggest a new automatic way to assist humans’ diagnosis, which could help supporting language rehabilitation for individuals with ASD in future.

Large-Scale Dialog Corpus Towards Automatic Mental Disease Diagnosis

Sakishita M., Kishimoto T., Takinami A., Eguchi Y., Kano Y., Studies in Computational Intelligence, 2020

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Recently, the number of people who are diagnosed as mental diseases is increasing. Efficient and objective diagnosis is important to start medical treatments in earlier stages. However, mental disease diagnosis is difficult to quantify criteria, because it is performed through conversations with patients, not by physical surveys. We aim to automate mental disease diagnosis in order to resolve these issues. We recorded conversations between psychologists and subjects to build our diagnosis speech corpus. Our subjects include healthy persons, people with mental diseases of depression, bipolar disorder, schizophrenia, anxiety and dementia. All of our subjects are diagnosed by doctors of psychiatry. Then we made accurate transcription manually, adding utterance time stamps, linguistic and non-linguistic annotations. Using our corpus, we performed feature analysis to find characteristics for each disease. We also tried automatic mental disease diagnosis by machine learning, while the number of sample data is few because we were still in our pilot study phase. We will increase the number of subjects in future.

情報通信技術（ICT）の活用. 講座 精神疾患の臨床 第1巻 気分症群

岸本泰士郎, 編集 神庭重信, 中山書店, 2020,  Page： 469-474

エッセンシャル金融ジェロントロジー

駒村 康平 編, 岸本 泰士郎,中村 陽一, 江口 洋子 著, 慶應義塾大学出版会, 2019.10

ゼロからわかる人工知能 仕事編, 医療と人工知能, Newton 別冊

岸本泰士郎, 株式会社ニュートンプレス, 2019.01

アセスメントにおけるITCの活用. 神経心理検査ベーシック改訂2版

木下翔太郎, 岸本泰士郎, 中外医学社, 2019,  Page： 343-350

AIドクターが命を救う　人工知能は医療をどう変えるか? Newton別冊

ショパン アントワン,岸本泰士郎, 狩野芳伸, 中村亮一, 浜本隆二, 株式会社ニュートンプレス, 2018.08

本田明編:精神科身体合併症マニュアル第２版

桑原達郎, 野村総一郎,岸本 泰士郎ほか, 医学書院, 2018.06

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