Takanori Yamashita

Scopus著者プロファイル

ウェブサイトhttps://hyoka.ofc.kyushu-u.ac.jp/search/details/K006931/index.html

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年別の研究成果

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フィンガープリント

Takanori Yamashitaが活動している研究トピックを掘り下げます。このトピックラベルは、この研究者の研究成果に基づきます。これらがまとまってユニークなフィンガープリントを構成します。

1 類似のプロファイル

11 会議への寄与
7 学術誌
1 会議記事

Artificial intelligence-derived gut microbiome as a predictive biomarker for therapeutic response to immunotherapy in lung cancer: protocol for a multicentre, prospective, observational study
Shoji, F., Yamashita, T., Kinoshita, F., Takamori, S., Fujishita, T., Toyozawa, R., Ito, K., Yamazaki, K., Nakashima, N. & Okamoto, T., 6月 8 2022, In: BMJ open. 12, 6, e061674.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読

Open Access
1 被引用数 (Scopus)
Machine learning for classification of postoperative patient status using standardized medical data
Yamashita, T., Wakata, Y., Nakaguma, H., Nohara, Y., Hato, S., Kawamura, S., Muraoka, S., Sugita, M., Okada, M., Nakashima, N. & Soejima, H., 2月 2022, In: Computer Methods and Programs in Biomedicine. 214, 106583.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読

Open Access
2 被引用数 (Scopus)
A functional learning health system in Japan: Experience with processes and information infrastructure toward continuous health improvement
Soejima, H., Matsumoto, K., Nakashima, N., Nohara, Y., Yamashita, T., Machida, J. & Nakaguma, H., 10月 2021, In: Learning Health Systems. 5, 4, e10252.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読

Open Access
1 被引用数 (Scopus)
Impact of a learning health system on acute care and medical complications after intracerebral hemorrhage
Matsumoto, K., Nohara, Y., Wakata, Y., Yamashita, T., Kozuma, Y., Sugeta, R., Yamakawa, M., Yamauchi, F., Miyashita, E., Takezaki, T., Yamashiro, S., Nishi, T., Machida, J., Soejima, H., Kamouchi, M. & Nakashima, N., 4月 2021, In: Learning Health Systems. 5, 2, e10223.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読

Open Access
5 被引用数 (Scopus)
Performance Verification of a Text Analyzer Using Machine Learning for Radiology Reports Toward Phenotyping
Yamashita, T., Izukura, R. & Nakashima, N., 2021, Innovation in Medicine and Healthcare - Proceedings of 9th KES-InMed 2021. Chen, Y-W., Chen, Y-W., Tanaka, S., Howlett, R. J., Howlett, R. J., Howlett, R. J., Jain, L. C. & Jain, L. C. (eds.). Springer Science and Business Media Deutschland GmbH, p. 171-182 12 p. (Smart Innovation, Systems and Technologies; vol. 242).
研究成果: 書籍/レポートタイプへの寄稿 › 会議への寄与

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詳細を開く

Artificial intelligence-derived gut microbiome as a predictive biomarker for therapeutic response to immunotherapy in lung cancer: protocol for a multicentre, prospective, observational study

Machine learning for classification of postoperative patient status using standardized medical data

A functional learning health system in Japan: Experience with processes and information infrastructure toward continuous health improvement

Impact of a learning health system on acute care and medical complications after intracerebral hemorrhage

Performance Verification of a Text Analyzer Using Machine Learning for Radiology Reports Toward Phenotyping

山下 貴範

フィンガープリント

ネットワーク

研究成果

Artificial intelligence-derived gut microbiome as a predictive biomarker for therapeutic response to immunotherapy in lung cancer: protocol for a multicentre, prospective, observational study

Machine learning for classification of postoperative patient status using standardized medical data

A functional learning health system in Japan: Experience with processes and information infrastructure toward continuous health improvement

Impact of a learning health system on acute care and medical complications after intracerebral hemorrhage

Performance Verification of a Text Analyzer Using Machine Learning for Radiology Reports Toward Phenotyping

山下貴範