KISHIMOTO Taishiro

写真a

Affiliation

School of Medicine, Hills Joint Research Laboratory for Future Preventive Medicine and Wellness (Shinanomachi)

Position

Project Professor (Non-tenured)

Related Websites

Profile Summary 【 Display / hide

Career 【 Display / hide

  • 2000.05
    -
    2001.03

    慶應義塾大学医学部, 精神神経科学教室, 研修医

  • 2001.04
    -
    2003.06

    国家公務員共済組合連合会 立川病院, 神経科

  • 2003.07
    -
    2004.03

    医療法人財団厚生協会 大泉病院

  • 2004.04
    -
    2009.11

    医療法人財団厚生協会 大泉病院, 副医長

  • 2009.04
    -
    2009.11

    医療法人財団厚生協会 大泉病院, 医長

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Academic Background 【 Display / hide

  • 1992.04

    The University of Tokyo, 理科 II 類

    University, Other

  • 1994.04
    -
    2000.03

    慶應義塾大学, 医学部

    University, Graduated

Academic Degrees 【 Display / hide

  • 慶應義塾大学, 慶応義塾大学, Coursework, 2009.02

Licenses and Qualifications 【 Display / hide

  • 医師免許, 2000.05

  • 精神保健指定医, 2005.12

  • 日本精神神経科学会 専門医, 2008.04

  • 日本英語検定 1級, 2014.07

  • 臨床精神神経薬理学 専門医, 2016.11

 

Books 【 Display / hide

  • 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

     View Summary

    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

     View Summary

    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.

  • 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

  • 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

    Scope: 307-313,331-334

  • 精神科の遠隔医療, 図説・日本の遠隔医療2017

    岸本 泰士郎, 一般社団法人 日本遠隔医療学会, 2017.12

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Papers 【 Display / hide

  • The characteristics of patients receiving psychotropic pro re nata medication at discharge for the treatment of schizophrenia and major depressive disorder: A nationwide survey from the EGUIDE project

    Ichihashi K., Kyou Y., Hasegawa N., Yasui-Furukori N., Shimizu Y., Hori H., Hashimoto N., Ide K., Imamura Y., Yamada H., Ochi S., Iga J.i., Takaesu Y., Ohi K., Tsuboi T., Iida H., Yamagata H., Hishimoto A., Horai T., Usami M., Makinodan M., Nagasawa T., Komatsu H., Kido M., Muraoka H., Atake K., Takeshima M., Kubota C., Inagaki T., Tamai S., Kishimoto T., Furihata R., Matsumoto J., Miura K., Inada K., Watanabe K., Kasai K., Hashimoto R.

    Asian Journal of Psychiatry (Asian Journal of Psychiatry)  69   103007 2022.03

    ISSN  18762018

     View Summary

    Background: Although several guidelines indicate that daily pharmacotherapy is an important part of the treatment of schizophrenia and major depressive disorder, there are few reports regarding pro re nata (PRN) prescriptions. The purpose of this study is to clarify the characteristics of patients receiving psychotropic PRN prescription for the treatment of schizophrenia and major depressive disorder. Method: We used data from ‘the effectiveness of guideline for dissemination and education in psychiatric treatment’ (EGUIDE) project to evaluate the presence or absence of psychotropic PRN prescription at the time of discharge, the age and sex of patients receiving PRN prescription for each diagnosis, and the association between PRN prescription and regular daily psychotropics. Results: The psychotropic PRN prescription ratio was 29.9% among 2617 patients with schizophrenia and 31.1% among 1248 patients with major depressive disorder at discharge. In schizophrenia, the psychotropic PRN prescription ratio was 21.6% for patients aged 65 years or older, which was lower than that of all other age groups. In major depressive disorder, the psychotropic PRN prescription ratio was 34.2% for female patients, which was significantly higher than that for male patients (25.5%). In schizophrenia, there was an association between psychotropic PRN prescription and regular use of multiple psychotropic medications. Conclusions: Psychotropic PRN prescription was less common in elderly patients with schizophrenia and more common in female patients with major depressive disorder. In schizophrenia, psychotropic PRN prescription led to polypharmacy of psychotropics. Further studies are needed to accumulate evidence and to provide education on appropriate PRN prescriptions.

  • Physical and mental health impact of COVID-19 on children, adolescents, and their families: The Collaborative Outcomes study on Health and Functioning during Infection Times - Children and Adolescents (COH-FIT-C&A)

    Solmi M., Estradé A., Thompson T., Agorastos A., Radua J., Cortese S., Dragioti E., Leisch F., Vancampfort D., Thygesen L.C., Aschauer H., Schloegelhofer M., Akimova E., Schneeberger A., Huber C.G., Hasler G., Conus P., Cuénod K.Q.D., von Känel R., Arrondo G., Fusar-Poli P., Gorwood P., Llorca P.M., Krebs M.O., Scanferla E., Kishimoto T., Rabbani G., Skonieczna-Żydecka K., Brambilla P., Favaro A., Takamiya A., Zoccante L., Colizzi M., Bourgin J., Kamiński K., Moghadasin M., Seedat S., Matthews E., Wells J., Vassilopoulou E., Gadelha A., Su K.P., Kwon J.S., Kim M., Lee T.Y., Papsuev O., Manková D., Boscutti A., Gerunda C., Saccon D., Righi E., Monaco F., Croatto G., Cereda G., Demurtas J., Brondino N., Veronese N., Enrico P., Politi P., Ciappolino V., Pfennig A., Bechdolf A., Meyer-Lindenberg A., Kahl K.G., Domschke K., Bauer M., Koutsouleris N., Winter S., Borgwardt S., Bitter I., Balazs J., Czobor P., Unoka Z., Mavridis D., Tsamakis K., Bozikas V.P., Tunvirachaisakul C., Maes M., Rungnirundorn T., Supasitthumrong T., Haque A., Brunoni A.R., Costardi C.G., Schuch F.B., Polanczyk G., Luiz J.M., Fonseca L., Aparicio L.V., Valvassori S.S., Nordentoft M., Vendsborg P., Hoffmann S.H., Sehli J., Sartorius N., Heuss S., Guinart D., Hamilton J., Kane J., Rubio J., Sand M.

    Journal of Affective Disorders (Journal of Affective Disorders)  299   367 - 376 2022.02

    ISSN  01650327

     View Summary

    Background: The COVID-19 pandemic has altered daily routines and family functioning, led to closing schools, and dramatically limited social interactions worldwide. Measuring its impact on mental health of vulnerable children and adolescents is crucial. Methods: The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT – www.coh-fit.com) is an on-line anonymous survey, available in 30 languages, involving >230 investigators from 49 countries supported by national/international professional associations. COH-FIT has thee waves (until the pandemic is declared over by the WHO, and 6–18 months plus 24–36 months after its end). In addition to adults, COH-FIT also includes adolescents (age 14–17 years), and children (age 6–13 years), recruited via non-probability/snowball and representative sampling and assessed via self-rating and parental rating. Non-modifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to promote health and prevent mental and physical illness in children and adolescents will be generated by COH-FIT. Co-primary outcomes are changes in well-being (WHO-5) and a composite psychopathology P-Score. Multiple behavioral, family, coping strategy and service utilization factors are also assessed, including functioning and quality of life. Results: Up to June 2021, over 13,000 children and adolescents from 59 countries have participated in the COH-FIT project, with representative samples from eleven countries. Limitations: Cross-sectional and anonymous design. Conclusions: Evidence generated by COH-FIT will provide an international estimate of the COVID-19 effect on children's, adolescents’ and families’, mental and physical health, well-being, functioning and quality of life, informing the formulation of present and future evidence-based interventions and policies to minimize adverse effects of the present and future pandemics on youth.

  • The collaborative outcomes study on health and functioning during infection times in adults (COH-FIT-Adults): Design and methods of an international online survey targeting physical and mental health effects of the COVID-19 pandemic

    Solmi M., Estradé A., Thompson T., Agorastos A., Radua J., Cortese S., Dragioti E., Leisch F., Vancampfort D., Thygesen L.C., Aschauer H., Schloegelhofer M., Akimova E., Schneeberger A., Huber C.G., Hasler G., Conus P., Cuénod K.Q.D., von Känel R., Arrondo G., Fusar-Poli P., Gorwood P., Llorca P.M., Krebs M.O., Scanferla E., Kishimoto T., Rabbani G., Skonieczna-Żydecka K., Brambilla P., Favaro A., Takamiya A., Zoccante L., Colizzi M., Bourgin J., Kamiński K., Moghadasin M., Seedat S., Matthews E., Wells J., Vassilopoulou E., Gadelha A., Su K.P., Kwon J.S., Kim M., Lee T.Y., Papsuev O., Manková D., Boscutti A., Gerunda C., Saccon D., Righi E., Monaco F., Croatto G., Cereda G., Demurtas J., Brondino N., Veronese N., Enrico P., Politi P., Ciappolino V., Pfennig A., Bechdolf A., Meyer-Lindenberg A., Kahl K.G., Domschke K., Bauer M., Koutsouleris N., Winter S., Borgwardt S., Bitter I., Balazs J., Czobor P., Unoka Z., Mavridis D., Tsamakis K., Bozikas V.P., Tunvirachaisakul C., Maes M., Rungnirundorn T., Supasitthumrong T., Haque A., Brunoni A.R., Costardi C.G., Schuch F.B., Polanczyk G., Luiz J.M., Fonseca L., Aparicio L.V., Valvassori S.S., Nordentoft M., Vendsborg P., Hoffmann S.H., Sehli J., Sartorius N., Heuss S., Guinart D., Hamilton J., Kane J., Rubio J., Sand M.

    Journal of Affective Disorders (Journal of Affective Disorders)  299   393 - 407 2022.02

    ISSN  01650327

     View Summary

    Background:. High-quality comprehensive data on short-/long-term physical/mental health effects of the COVID-19 pandemic are needed. Methods:. The Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) is an international, multi-language (n=30) project involving >230 investigators from 49 countries/territories/regions, endorsed by national/international professional associations. COH-FIT is a multi-wave, on-line anonymous, cross-sectional survey [wave 1: 04/2020 until the end of the pandemic, 12 months waves 2/3 starting 6/24 months threreafter] for adults, adolescents (14-17), and children (6-13), utilizing non-probability/snowball and representative sampling. COH-FIT aims to identify non-modifiable/modifiable risk factors/treatment targets to inform prevention/intervention programs to improve social/health outcomes in the general population/vulnerable subgrous during/after COVID-19. In adults, co-primary outcomes are change from pre-COVID-19 to intra-COVID-19 in well-being (WHO-5) and a composite psychopathology P-Score. Key secondary outcomes are a P-extended score, global mental and physical health. Secondary outcomes include health-service utilization/functioning, treatment adherence, functioning, symptoms/behaviors/emotions, substance use, violence, among others. Results:. Starting 04/26/2020, up to 14/07/2021 >151,000 people from 155 countries/territories/regions and six continents have participated. Representative samples of ≥1,000 adults have been collected in 15 countries. Overall, 43.0% had prior physical disorders, 16.3% had prior mental disorders, 26.5% were health care workers, 8.2% were aged ≥65 years, 19.3% were exposed to someone infected with COVID-19, 76.1% had been in quarantine, and 2.1% had been COVID 19-positive. Limitations:. Cross-sectional survey, preponderance of non-representative participants. Conclusions:. Results from COH-FIT will comprehensively quantify the impact of COVID-19, seeking to identify high-risk groups in need for acute and long-term intervention, and inform evidence-based health policies/strategies during this/future pandemics.

  • Current Status and Challenges of the Dissemination of Telemedicine in Japan After the Start of the COVID-19 Pandemic

    Kinoshita Shotaro, Kishimoto Taishiro

    TELEMEDICINE AND E-HEALTH  2021.12

    ISSN  1530-5627

  • Japanese project for telepsychiatry evaluation during COVID-19: Treatment comparison trial (J-PROTECT): Rationale, design, and methodology

    Kishimoto T., Kinoshita S., Bun S., Sato Y., Kitazawa M., Kikuchi T., Sado M., Takamiya A., Mimura M., Nakamae T., Abe Y., Kanazawa T., Kawabata Y., Tomita H., Abe K., Hishimoto A., Asami T., Suda A., Watanabe Y., Amagai T., Sakuma K., Kida H., Funayama M., Kimura H., Sato A., Fujiwara S., Nagao K., Sugiyama N., Takamiya M., Kodama H., Azekawa T.

    Contemporary Clinical Trials (Contemporary Clinical Trials)  111   106596 2021.12

    ISSN  15517144

     View Summary

    Introduction: The COVID-19 pandemic has had a profound impact on the mental health of people around the world. Anxiety related to infection, stress and stigma caused by the forced changes in daily life have reportedly increased the incidence and symptoms of depression, anxiety disorder and obsessive-compulsive disorder. Under such circumstances, telepsychiatry is gaining importance and attracting a great deal of attention. However, few large pragmatic clinical trials on the use of telepsychiatry targeting multiple psychiatric disorders have been conducted to date. Methods: The targeted study cohort will consist of adults (>18 years) who meet the DSM-5 diagnostic criteria for either (1) depressive disorders, (2) anxiety disorders, or (3) obsessive-compulsive and related disorders. Patients will be assigned in a 1:1 ratio to either a “telepsychiatry group” (at least 50% of treatments to be conducted using telemedicine, with at least one face-to-face treatment [FTF] within six months) or an “FTF group” (all treatments to be conducted FTF, with no telemedicine). Both groups will receive the usual treatment covered by public medical insurance. The study will utilize a master protocol design in that there will be primary and secondary outcomes for the entire group regardless of diagnosis, as well as the outcomes for each individual disorder group. Discussion: This study will be a non-inferiority trial to test that the treatment effect of telepsychiatry is not inferior to that of FTF alone. This study will provide useful insights into the effect of the COVID-19 pandemic on the practice of psychiatry. Trial Registration: jRCT1030210037, Japan Registry of Clinical Trials (jRCT).

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Papers, etc., Registered in KOARA 【 Display / hide

Reviews, Commentaries, etc. 【 Display / hide

  • 【COVID-19がメンタルヘルスに与える影響】COVID-19による精神科診療システムへの影響

    木下 翔太郎, 岸本 泰士郎

    臨床精神薬理 ((株)星和書店)  24 ( 10 ) 1023 - 1030 2021.10

    ISSN  1343-3474

     View Summary

    新型コロナウイルス感染症(COVID-19)のパンデミックは、多くの人々のメンタルヘルスにも悪影響を与えるとともに、生活様式にも大きな影響をもたらした。このような状況の中で、感染対策の一つとして遠隔医療が注目されるようになり、パンデミック下において医療を継続するための手段として世界中で利用が拡大している。我が国においては、法的規制の問題から遠隔医療の普及は遅れていたが、パンデミック下において、特例的な規制緩和が行われ、普及が加速しつつある。精神科領域でも実施可能な範囲が大きく広がっているが、対面診療よりも低く設定された診療報酬や初診において処方可能な薬剤の制限など課題も多く、導入の障壁となっているとみられる。本稿では、パンデミック下における我が国の遠隔医療と薬物療法に関する規制動向や海外との比較、今後の展望について述べる。(著者抄録)

  • AIは精神科臨床に何をもたらすか?精神医学、工学、社会科学的側面からの考察 AI技術を活用したうつ病症状の定量化

    岸本 泰士郎

    精神神経学雑誌 ((公社)日本精神神経学会)   ( 2021特別号 ) S488 - S488 2021.09

    ISSN  0033-2658

  • 精神科領域でのオンライン診療の進展:現状と今後 オンライン診療や遠隔モニタリングを活用した近未来の精神科医療の展望 臨床研究のレビューを中心に

    岸本 泰士郎

    精神神経学雑誌 ((公社)日本精神神経学会)   ( 2021特別号 ) S377 - S377 2021.09

    ISSN  0033-2658

  • コロナ時代の遠隔神経心理学的検査のあり方 本邦におけるオンライン診療導入経過とエビデンス

    岸本 泰士郎

    日本神経心理学会総会プログラム・予稿集 (日本神経心理学会)  45回   76 - 76 2021.09

  • 【精神科病院における外来機能の再考】精神科における遠隔医療の可能性

    木下 翔太郎, 岸本 泰士郎

    日本精神科病院協会雑誌 ((公社)日本精神科病院協会)  40 ( 9 ) 42 - 47 2021.09

    ISSN  1347-4103

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Presentations 【 Display / hide

  • Perspectives in machine learning for predicting psychiatric conditions.

    TAISHIRO KISHIMOTO

    WFSBP 2018 KOBE (KOBE) , 

    2018.09

    Oral presentation (invited, special)

  • ICTや機械学習を活用した精神科領域における重症度評価の試み

    TAISHIRO KISHIMOTO

    がん分子修飾制御学分野主催セミナー (東京) , 

    2018.08

    Oral presentation (invited, special)

  • 情報処理技術(ICT)や機械学習を用いたうつ病診療の展望

    TAISHIRO KISHIMOTO

    第3回CNSサミット (東京) , 

    2018.08

    Oral presentation (invited, special)

  • 情報通信技術(ICT)や機械学習を用いたうつ病診療の展望

    TAISHIRO KISHIMOTO

    第3回CNSサミット, 

    2018.08

    Oral presentation (invited, special)

  • ビデオ会議システムを用いた遠隔認知行動療法の開発:認知行動療法の普及を (実践発表) 見据えて

    TAISHIRO KISHIMOTO

    第15回日本うつ病学会総会, 

    2018.07

    Poster presentation

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • 令和3年度 医工連携・人工知能実装研究事業「リストバンド型ウェアラブルデバイスデータを用いてうつ病スクリーニングおよび重症度評価を可能とするソフトウェア医療機器の開発」

    2021
    -
    Present

    日本医療研究開発機構(AMED, Commissioned research, Principal investigator

  • KGRI-IoT健康ライフ研究コンソーシアム「脳波を用いた認知機能評価基準の定量化」(研究代表者)

    2020
    -
    Present

    Consortium, Principal investigator

  • 障害者対策総合研究開発事業(精神障害分野)「対面診療に比したオンライン診療の非劣勢試験:COVID-19によって最も影響を受け得る精神疾患に対するマスタープロトコル試験による検証」

    2020
    -
    Present

    日本医療研究開発機構(AMED), Commissioned research, Principal investigator

  • 障害者対策総合研究開発事業(精神障害分野)「認知行動療法の治療最適化ツールと客観的効果判定指標の開発」

    2019
    -
    Present

    日本医療研究開発機構(AMED), Commissioned research, Coinvestigator(s)

  • 戦略的創造研究推進事業(CREST)「精神医学×メディア解析技術による心の病の定量化・早期発見と社会サービスの創出」

    2019
    -
    Present

    国立研究開発法人科学技術振興機構(JST), Commissioned research, Coinvestigator(s)

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Awards 【 Display / hide

  • 2019年度 慶應医学賞 ライジング・スター賞

    2020.01, 慶應義塾大学

  • Keio Techno Mall Lion Award(研究室として受賞)

    2017.12

  • 国際学会発表賞

    2014.06, 第110回日本精神神経科学会学術総会

  • 国際学会発表賞

    2014.06, 日本精神神経科学会

  • Japanese Society of Neuropsychopharmacology Excellent Presentation Award for CINP 2014

    2014.06, CINP 2014

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Courses Taught 【 Display / hide

  • LECTURE SERIES, PSYCHIATRY

    2022

  • LECTURE SERIES, PSYCHIATRY

    2021

  • LECTURE SERIES, PSYCHIATRY

    2020

  • LECTURE SERIES, PSYCHIATRY

    2019

 

Social Activities 【 Display / hide

  • 厚生労働省 平成25年度 障害者総合福祉推進事業 「精神病床に入院している難治性患者の地域移行の推進に向けた支援の在り方に関する実態調査」研究分担者・実務担当者

    2014
    -
    Present

Memberships in Academic Societies 【 Display / hide

  • 保健医療分野におけるAI活用推進懇談会 構成員, 

    2017
    -
    Present
  • 独立行政法人医薬品医療機器総合機構専門委員, 

    2017
    -
    2019
  • 第14回日本うつ病学会総会プログラム委員, 

    2016
    -
    Present
  • 日本総合病院精神医学会 会員 (2016~ プログラム委員), 

    2015
    -
    Present
  • 日本遠隔医療学会 (2016~ 精神科分科会代表), 

    2014
    -
    Present

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Committee Experiences 【 Display / hide

  • 2018.08
    -
    2019.03

    プログラム委員, 第41回日本生物学精神医学会

  • 2018.08
    -
    2019.03

    委員, 総務省 オンライン診療の普及促進に向けたモデル構築にかかる調査研究検討委員会

  • 2018.05
    -
    Present

    評議員, 一般社団法人日本メディカルAI学会

  • 2017
    -
    Present

    構成員, 保健医療分野におけるAI活用推進懇談会

  • 2017
    -
    2019

    専門委員, 独立行政法人医薬品医療機器総合機構

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