東北大学大学院医学系研究科・医学部

STAFF

Professor

• Yamamoto YoichiroProfessor. 山本　陽一朗 教授
  

CONTACT

OUTLINE

Our ultimate goal is to discover novel disease mechanisms, to find new therapies or to choose the best treatment for each patient through the combination of the state-of-the-art AI technology and medical big data including multiscale information, which provides the link between molecular biology and clinical medicine. We establish a comprehensive analysis of medical information through collaboration with clinical doctors, which will contribute to the cure of currently incurable patients.

医療画像や臨床データ等を含む多階層の医療ビッグデータに対して、最新の人工知能と数理解析、医学分野における先人の叡智を結び付けた解析を行っています。未だ明らかになっていない疾患メカニズムの解明や、新規治療法の発見、また患者さん毎に最適な治療方法を選択するシステムの開発を研究目的とし、臨床の現場と協力しながら、医学データの統合的解析を進めることで、患者さんの治療に役に立つ研究を進めていきます。

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  理化学研究所革新知能統合研究(AIP)センター（日本橋、東京）にて。
  At RIKEN Center for Advanced Intelligence Project (AIP), Tokyo.

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  前立腺病理標本の連続切片に対するAI解析
  AI analysis on serial sections of prostate pathology specimens.

ARTICLE

Akatsuka J, et.al. A data-driven ultrasound approach discriminates pathological high grade prostate cancer. Scientific Reports 12(1) 860-860 2022.
URL：https://www.nature.com/articles/s41598-022-04951-3

Egevad L, et.al. The emerging role of artificial intelligence in the reporting of prostate pathology. Pathology 53(5):565-567, 2021.
URL：https://doi.org/10.1016/j.pathol.2021.04.002

Yamamoto Y, et.al. Automated acquisition of explainable knowledge from unannotated histopathology images. Nature Communications 10(1):5642-5642, 2019.
URL：https://www.nature.com/articles/s41467-019-13647-8

Yamamoto Y, et.al. Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach. Scientific Reports 7:46732, 2017.
URL：https://www.nature.com/articles/srep46732

Yamamoto Y, et.al. Tumour and immune cell dynamics explain the PSA bounce after prostate cancer brachytherapy. British Journal of Cancer 115(2):195-202, 2016.
URL：https://www.nature.com/articles/bjc2016171