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J-GLOBAL ID：202001020325383450 Update date: Feb. 26, 2025

Ishikawa Tetsuo

イシカワテツオ | Ishikawa Tetsuo

Affiliation and department：
Job title： Associate Professor

Research field (1)： Cognitive neuroscience

Research theme for competitive and other funds (2)：

2021 - 2025 『生体リズムに着目した発達障害の解析ー胎児期から幼児期までの縦断研究ー』
2020 - 2023 Visualization and prediction of health and disease states using landscape models

Papers (32)：

石川哲朗. エネルギーランドスケープ解析による生活習慣病の発症過程と未病状態の可視化. 月刊バイオインダストリー. 2025. 42. 2
Multifactorial Assessment of Complication Risks in Embolization for Ruptured Cerebral Aneurysm. 2025. 19. 1. oa.2024-0095
Medical AI and AI for Medical Sciences. 2025. 8. 1. 26-37
Tetsuo Ishikawa, Masahiro Shinoda, Megumi Oya, Koichi Ashizaki, Shinichiro Ota, Kenichi Kamachi, Kazuhiro Sakurada, Eiryo Kawakami, Masaharu Shinkai. Explainable machine learning framework for dynamic monitoring of disease prognostic risk (Preprint). 2024
Akiko Hanai, Tetsuo Ishikawa, Shoichiro Kawauchi, Yuta Iida, Eiryo Kawakami. Generative artificial intelligence and non-pharmacological bias: an experimental study on cancer patient sexual health communications. BMJ Health & Care Informatics. 2024. 31. 1. e100924

MISC (9)：

小口真司, 小口真司, 石川哲朗, 石川哲朗, 華井明子, 華井明子, 加藤大吾, 板倉昭二, 奥野昌子, 渡部基信, et al. Comprehensive Analysis of Sleep Dynamics in Children via non-negative tensor factorization. 日本小児科学会雑誌. 2024. 128. 2
華井明子, 華井明子, 石川哲朗, 石川哲朗, 石川哲朗, 川内翔一朗, 飯田裕太, 川上英良, 川上英良. 情報提供ツールとしてのGenerative Artificial Intelligenceの有用性の検討. 日本サイコオンコロジー学会総会(Web). 2023. 36th
千田克幸, 千田克幸, 石川哲朗, 石川哲朗, 石川哲朗, 華井明子, 華井明子, 花之枝彩香, 柏木佑介, 佐藤潤弥, et al. Elucidation of synergistic risk factors for nephrotic syndrome based on time-series statistical evaluation of comorbidities. 日本薬学会年会要旨集(Web). 2023. 143rd
川上英良, 石川哲朗, 華井明子, 大矢めぐみ. 衛生学の発展に向けた先制医療の可能性を考える予防・先制医療に向けたデータ駆動型アプローチ. 日本衛生学雑誌. 2022. 77. Suppl. S139-S139
川上英良, 川上英良, 石川哲朗, 華井明子, 大矢めぐみ, 大矢めぐみ. 予防・先制医療に向けたデータ駆動型アプローチ. 日本衛生学雑誌(Web). 2022. 77. Supplement

Patents (3)：

Books (1)：

CARLS Series of Advanced Study of Logic and Sensibility Vol.4
Keio University Press 2011

Lectures and oral presentations (100)：

Neuroanatomical Subtypes Indicate Treatment Resistance in Schizophrenia.
(63rd Annual Meeting of the American College of Neuropsychopharmacology (ACNP), Phoenix, Arizona, USA)
Application of machine learning in clustering and prediction models for recurrence in fertility-sparing therapy for endometrial cancer and atypical endometrial hyperplasia.
(Asian Society of Gynecologic Oncology (ASGO) Meeting, Bali, Indonesia 2024)
データ駆動型機械学習アプローチによる加齢関連遺伝子の包括的探索と可視化
(第47回日本分子生物学会年会 2024)
臨床医がAI技術を理解する意義
(第40回日本脳神経血管内治療学会学術集会(JSNET2024), 熊本 2024)
Machine Learning to Predict the Risk of Incident Diabetic macular edema Among Patients With Diabetes
(1st Asia & Pacific Bioinformatics Joint Conference (APBJC2024), Okinawa, Japan)

Education (3)：

Work history (16)：

2024/10 - 現在 Institute of Science Tokyo
2024/10 - 現在大阪大学 D3センター招へい研究員
2023/05 - 現在 The University of Tokyo
2022/04 - 現在野村皮膚科医院客員研究員
2022/04 - 現在 Keio University School of Medicine Department of Extended Intelligence for Medicine, The Ishii-Ishibashi Laboratory Associate Professor

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Awards (5)：

2024/06 - 日本皮膚科学会第123回総会優秀演題賞
2023/10 - 第36回日本サイコオンコロジー学会総会優秀演題賞
2023/02 - 日本皮膚科学会アトピー性皮膚炎臨床研究奨励賞学会発表賞
2020/06 - 日本皮膚科学会第119回総会優秀演題賞
2020/03 - RIKEN Ohbu Industry Partnerships Incentive Award "State visualization device, state visualization method and state visualization program"

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