Research Summary

Research Subjects

Selected Publications

Papers with an asterisk(*) are based on research conducted outside of RIKEN.

• 1. Noguchi A, Numata Y, Sugawara T, Miura H, Konno K, Adachi Y, Yamaguchi R, Ishida M, Kokumai T, Daisuke D, Miura T, Maeda S, Otsuka H, Mizuma M, Nakagawa K, Morikawa H, Akatsuka J, Maeda I, Unno, M Yamamoto Y, Toru Furukawa T.:
  "Deep learning predicts 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology."
  Sci Rep. 14, 17059 (2024).
• 2. Yamaguchi R, Morikawa H, Akatsuka J, Numata Y, Noguchi A, Kokumai T, Ishida M, Mizuma M, Morikawa T, Unno M, Miyake A, Tamiya G, Yamamoto Y, Toru Furukawa T.:
  "Machine learning of histopathological images predicts recurrences of resected pancreatic ductal adenocarcinoma with adjuvant treatment."
  Pancreas. 53(2), e199-e204 (2023).
• 3. Takahashi T, Matsuoka H, Sakurai R, Akatsuka J, Kobayashi Y, Nakamura M, Iwata T, Banno K, Matsuzaki M, Takayama J, Aoki D, Yamamoto Y, Tamiya G.:
  "Development of a prognostic prediction support system for cervical intraepithelial neoplasia using artificial intelligence-based diagnosis."
  J Gynecol Oncol. 33(5), e57 (2022).
• 4. Akatsuka J, Numata Y, Morikawa H, Sekine T, Kayama S, Mikami H, Yanagi M, Endo Y, Takeda H, Toyama Y, Fukumoto M, Kimura G, Kondo Y, Yamamoto Y.:
  "A data-driven ultrasound approach for pathological high-grade prostate cancer."
  Sci Rep. 12(1), 860-860 (2022).
• 5. Egevad L, Delahunt B, Samaratunga H, Tsuzuki T, Yamamoto Y, Yaxley J, Ruusuvuori P, Kartasalo K, Eklund M.:
  "The emerging role of artificial intelligence in the reporting of prostate pathology."
  Pathology 53(5):565-567, (2021).
• 6. Yamamoto Y, Tsuzuki T, Akatsuka J, Ueki M, Morikawa H, Numata Y, Takahara T, Tsuyuki T, Tsutsumi K, Nakazawa R, Shimizu A, Maeda I, Tsuchiya S, Kanno H, Kondo Y, Fukumoto M, Tamiya G, Ueda N, Kimura G.:
  "Automated acquisition of explainable knowledge from unannotated histopathology images."
  Nat Commun. 10, 5642 (2019).
• 7. Akatsuka J, Yamamoto Y, Sekine T, Numata Y, Morikawa H, Tsutsumi K, Yanagi M, Endo Y, Takeda H, Hayashi T, Ueki M, Tamiya G, Maeda I, Fukumoto M, Shimizu A, Tsuzuki T, Kimura G, Kondo Y.:
  "Illuminating Clues of Cancer Buried in Prostate MR Image: Deep Learning and Expert Approaches."
  Biomolecules. 9, 673 (2019).
• 8. Yamamoto Y, Saito A, Tateishi A, Shimojo H, Kanno H, Tsuchiya S, Ito KI, Cosatto E, Graf HP, Moraleda RR, Eils R, and Grabe N.:
  "Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach."
  Sci Rep. 7, 46732 (2017).
• 9. *Yamamoto Y, Offord CP, Kimura G, Kuribayashi S, Takeda H, Tsuchiya S, Shimojo H, Kanno H, Bozic I, Nowak MA, Bajzer ž, and Dingli D.:
  "Tumor and immune cell dynamics explain the PSA bounce after prostate cancer brachytherapy."
  Br J Cancer. 115, 195-202 (2016).
• 10. *Saito A, Numata Y, Hamada T, Horisawa T, Cosatto E, Graf HP, Kuroda M, and Yamamoto Y.:
  "A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix."
  J Pathol Inform. 7, 36 (2016).

Recent Research Results

• 

  Mar. 19, 2020
  New clues in AI cancer prognoses

• 

  Dec. 18, 2019
  Artificial intelligence identifies previously unknown features associated with cancer recurrence

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