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Computational analysis of morphological and molecular features in gastric cancer tissues

  • Published:2020-02-03 Issue:6 Volume:9 Page:2223-2234
  • ISSN:2045-7634
  • Container-title:Cancer Medicine
  • language:en
  • Short-container-title:Cancer Med

Author:

Yasuda Yoko12,Tokunaga Kazuaki1,Koga Tomoaki1,Sakamoto Chiyomi1,Goldberg Ilya G.3,Saitoh Noriko4,Nakao Mitsuyoshi1ORCID

Affiliation:

1. Department of Medical Cell Biology Institute of Molecular Embryology and Genetics Kumamoto University Kumamoto Japan

2. Department of Health Science Faculty of Medical Science Kyushu University Fukuoka Japan

3. Image Informatics and Computational Biology Unit Laboratory of Genetics National Institute on Aging National Institutes of Health Baltimore MD USA

4. The Cancer Institute of JFCR Tokyo Japan

Funder

Naito Foundation

Mitsubishi Foundation

Japan Society for the Promotion of Science

Japan Agency for Medical Research and Development

Publisher

Wiley

Subject

Cancer Research,Radiology Nuclear Medicine and imaging,Oncology

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1. A Review on framework to Detect and Diagnose Body System based Cancer using deep Learning Techniques;2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE);2023-05-12

2. Artificial intelligence applications in predicting the behavior of gastrointestinal cancers in pathology;Artificial Intelligence in Gastroenterology;2022-12-28

3. Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers;Cancers;2022-08-03

4. Application of deep learning in image recognition and diagnosis of gastric cancer;Artificial Intelligence in Gastrointestinal Endoscopy;2021-04-28

5. Molecular Chaperones and Thyroid Cancer;International Journal of Molecular Sciences;2021-04-18
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