{"title":"日本制药商协会非临床评价专家委员会人工智能病理学工作组报告:关于人工智能病理学的最新出版物概述。","authors":"Emi Tomikawa, Satoshi Sakai, Yoshinori Yamagiwa, Yumi Kangawa, Yusuke Kagawa, Yuki Kato, Kensuke Kojima, Akira Inomata, Izumi Matsumoto, Gen Sato, Mutsumi Suzuki","doi":"10.1293/tox.2024-0100","DOIUrl":null,"url":null,"abstract":"<p><p>The use of artificial intelligence (AI) in non-clinical pathology is rapidly expanding. In this study, we conducted a literature survey of articles published after 2017 that used AI to analyze the histopathological images of experimental animals. We identified 44 articles that used AI for various purposes, including the detection of abnormal sites, determination and quantification of normal tissues, and classification of normal/abnormal images. AI systems or applications were either custom-built, commercially available, or a combination of both. Rats and mice were mainly used, and the liver was the most frequently analyzed organ. Our findings suggest that AI can be useful in non-clinical pathology and that collaboration between pharmaceutical companies or cooperation with IT experts can be a potential approach to further advance the utilization of AI in this field.</p>","PeriodicalId":17437,"journal":{"name":"Journal of Toxicologic Pathology","volume":"38 3","pages":"191-198"},"PeriodicalIF":0.9000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208865/pdf/","citationCount":"0","resultStr":"{\"title\":\"Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: an overview of recent publications about AI pathology.\",\"authors\":\"Emi Tomikawa, Satoshi Sakai, Yoshinori Yamagiwa, Yumi Kangawa, Yusuke Kagawa, Yuki Kato, Kensuke Kojima, Akira Inomata, Izumi Matsumoto, Gen Sato, Mutsumi Suzuki\",\"doi\":\"10.1293/tox.2024-0100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The use of artificial intelligence (AI) in non-clinical pathology is rapidly expanding. In this study, we conducted a literature survey of articles published after 2017 that used AI to analyze the histopathological images of experimental animals. We identified 44 articles that used AI for various purposes, including the detection of abnormal sites, determination and quantification of normal tissues, and classification of normal/abnormal images. AI systems or applications were either custom-built, commercially available, or a combination of both. Rats and mice were mainly used, and the liver was the most frequently analyzed organ. Our findings suggest that AI can be useful in non-clinical pathology and that collaboration between pharmaceutical companies or cooperation with IT experts can be a potential approach to further advance the utilization of AI in this field.</p>\",\"PeriodicalId\":17437,\"journal\":{\"name\":\"Journal of Toxicologic Pathology\",\"volume\":\"38 3\",\"pages\":\"191-198\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208865/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Toxicologic Pathology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1293/tox.2024-0100\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Toxicologic Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1293/tox.2024-0100","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/11 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PATHOLOGY","Score":null,"Total":0}
Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: an overview of recent publications about AI pathology.
The use of artificial intelligence (AI) in non-clinical pathology is rapidly expanding. In this study, we conducted a literature survey of articles published after 2017 that used AI to analyze the histopathological images of experimental animals. We identified 44 articles that used AI for various purposes, including the detection of abnormal sites, determination and quantification of normal tissues, and classification of normal/abnormal images. AI systems or applications were either custom-built, commercially available, or a combination of both. Rats and mice were mainly used, and the liver was the most frequently analyzed organ. Our findings suggest that AI can be useful in non-clinical pathology and that collaboration between pharmaceutical companies or cooperation with IT experts can be a potential approach to further advance the utilization of AI in this field.
期刊介绍:
JTP is a scientific journal that publishes original studies in the field of toxicological pathology and in a wide variety of other related fields. The main scope of the journal is listed below.
Administrative Opinions of Policymakers and Regulatory Agencies
Adverse Events
Carcinogenesis
Data of A Predominantly Negative Nature
Drug-Induced Hematologic Toxicity
Embryological Pathology
High Throughput Pathology
Historical Data of Experimental Animals
Immunohistochemical Analysis
Molecular Pathology
Nomenclature of Lesions
Non-mammal Toxicity Study
Result or Lesion Induced by Chemicals of Which Names Hidden on Account of the Authors
Technology and Methodology Related to Toxicological Pathology
Tumor Pathology; Neoplasia and Hyperplasia
Ultrastructural Analysis
Use of Animal Models.