Hidetaka Arimura

Scopus著者プロファイル

ウェブサイトhttps://hyoka.ofc.kyushu-u.ac.jp/html/100019481_ja.html

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年別の研究成果

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Hidetaka Arimura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

115 学術誌
39 会議への寄与
6 会議記事
6 総説
その他

Corrigendum to “Topological radiogenomics based on persistent lifetime images for identification of epidermal growth factor receptor mutation in patients with non-small cell lung tumors” [Computers in Biology and Medicine. 185 (2025) 109519] (Computers in Biology and Medicine (2025) 185, (S0010482524016044), (10.1016/j.compbiomed.2024.109519))
Kodama, T., Arimura, H., Tokuda, T., Tanaka, K., Yabuuchi, H., Muhammad Gowdh, N. F., Liam, C. K., Chai, C. S. & Ng, K. H., 4月 2025, In: Computers in Biology and Medicine. 188, 109860.
研究成果: ジャーナルへの寄稿 › コメント/討論 › 査読
Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography
Hamasaki, H., Arimura, H., Yamasaki, Y., Yamamoto, T., Fukata, M., Matoba, T., Kato, T. & Ishigami, K., 2025, (印刷中) In: Physical and Engineering Sciences in Medicine.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読
Topological radiogenomics based on persistent lifetime images for identification of epidermal growth factor receptor mutation in patients with non-small cell lung tumors
Kodama, T., Arimura, H., Tokuda, T., Tanaka, K., Yabuuchi, H., Gowdh, N. F. M., Liam, C. K., Chai, C. S. & Ng, K. H., 2月 2025, In: Computers in Biology and Medicine. 185, 109519.
研究成果: ジャーナルへの寄稿 › 学術誌 › 査読

Open Access
Erratum: Correction: Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant Betti numbers (PloS one (2021) 16 1 DOI: 10.1371/journal.pone.0244354)
Ninomiya, K., Arimura, H., Chan, W. Y., Tanaka, K., Mizuno, S., Muhammad Gowdh, N. F., Yaakup, N. A., Liam, C. K., Chai, C. S. & Ng, K. H., 2024, In: PloS one. 19, 12, p. e0316496
研究成果: ジャーナルへの寄稿 › コメント/討論 › 査読

Open Access
Prediction of Consolidation Tumor Ratio on Planning CT Images of Lung Cancer Patients Treated with Radiotherapy Based on Deep Learning
Tong, Y., Arimura, H., Yoshitake, T., Cui, Y., Kodama, T., Shioyama, Y., Wirestam, R. & Yabuuchi, H., 4月 2024, In: Applied Sciences (Switzerland). 14, 8, 3275.
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)

有村秀孝

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過去5年の共同研究と上位研究分野

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Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography

Topological radiogenomics based on persistent lifetime images for identification of epidermal growth factor receptor mutation in patients with non-small cell lung tumors

Erratum: Correction: Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant Betti numbers (PloS one (2021) 16 1 DOI: 10.1371/journal.pone.0244354)

Prediction of Consolidation Tumor Ratio on Planning CT Images of Lung Cancer Patients Treated with Radiotherapy Based on Deep Learning

有村 秀孝

フィンガープリント

過去5年の共同研究と上位研究分野

研究成果

Noninvasive machine-learning models for the detection of lesion-specific ischemia in patients with stable angina with intermediate stenosis severity on coronary CT angiography

Topological radiogenomics based on persistent lifetime images for identification of epidermal growth factor receptor mutation in patients with non-small cell lung tumors

Erratum: Correction: Robust radiogenomics approach to the identification of EGFR mutations among patients with NSCLC from three different countries using topologically invariant Betti numbers (PloS one (2021) 16 1 DOI: 10.1371/journal.pone.0244354)

Prediction of Consolidation Tumor Ratio on Planning CT Images of Lung Cancer Patients Treated with Radiotherapy Based on Deep Learning

有村秀孝