Komura, Daisuke

The repertoire of mutational signatures in human cancer

Alexandrov, L. B., Kim, J., Haradhvala, N. J., Huang, M. N., Tian Ng, A. W., Wu, Y., Boot, A., Covington, K. R., Gordenin, D. A., Bergstrom, E. N., et al. (2020) · Nature

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

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Pan-cancer analysis of whole genomes

The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, Aaltonen, L. A., Abascal, F., Abeshouse, A., Aburatani, H., Adams, D. J., Agrawal, N., Ahn, K. S., Ahn, S.-M., Aikata, H., et al. (2020) · Nature

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 3,064

The evolutionary history of 2,658 cancers

Gerstung, M., Jolly, C., Leshchiner, I., Dentro, S. C., Gonzalez, S., Rosebrock, D., Mitchell, T. J., Rubanova, Y., Anur, P., Yu, K., et al. (2020) · Nature

Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer

Cited by 1,057

Machine Learning Methods for Histopathological Image Analysis

Komura, D., & Ishikawa, S. (2018) · Computational and Structural Biotechnology Journal

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 937

Patterns of somatic structural variation in human cancer genomes

Li, Y., Roberts, N. D., Wala, J. A., Shapira, O., Schumacher, S. E., Kumar, K., Khurana, E., Waszak, S., Korbel, J. O., Haber, J. E., et al. (2020) · Nature

Cancer Genomics and DiagnosticsGenomic variations and chromosomal abnormalities

Cited by 867

Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

Cortés-Ciriano, I., Lee, J. J.-K., Xi, R., Jain, D., Jung, Y. L., Yang, L., Gordenin, D., Klimczak, L. J., Zhang, C.-Z., Pellman, D. S., et al. (2020) · Nature Genetics

Cancer Genomics and DiagnosticsGenomic variations and chromosomal abnormalities

Cited by 712

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

Bandi, P., Geessink, O., Manson, Q., Van Dijk, M., Balkenhol, M., Hermsen, M., Ehteshami Bejnordi, B., Lee, B., Paeng, K., Zhong, A., et al. (2019) · IEEE Transactions on Medical Imaging

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 569

Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition

Rodriguez-Martin, B., Alvarez, E. G., Baez-Ortega, A., Zamora, J., Supek, F., Demeulemeester, J., Santamarina, M., Ju, Y. S., Temes, J., Garcia-Souto, D., et al. (2020) · Nature Genetics

Genomic variations and chromosomal abnormalitiesCancer Genomics and Diagnostics

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Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer

Akdemir, K. C., Le, V. T., Chandran, S., Li, Y., Verhaak, R. G., Beroukhim, R., Campbell, P. J., Chin, L., Dixon, J. R., Futreal, P. A., et al. (2020) · Nature Genetics

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 283

A multimodal whole-slide foundation model for pathology

Ding, T., Wagner, S. J., Song, A. H., Chen, R. J., Lu, M. Y., Zhang, A., Vaidya, A. J., Jaume, G., Shaban, M., Kim, A., et al. (2025) · Nature Medicine

AI in cancer detectionMultimodal Machine Learning Applications

Cited by 171

Machine learning methods for histopathological image analysis: updates in 2024

Komura, D., Ochi, M., & Ishikawa, S. (2025) · Computational and Structural Biotechnology Journal

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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