{"title":"Artificial Intelligence and Lung Pathology.","authors":"Emanuel Caranfil, Kris Lami, Wataru Uegami, Junya Fukuoka","doi":"10.1097/PAP.0000000000000448","DOIUrl":null,"url":null,"abstract":"<p><p>This manuscript provides a comprehensive overview of the application of artificial intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses various AI models designed to support pathologists and clinicians. AI models supporting pathologists are to standardize diagnosis, score PD-L1 status, supporting tumor cellularity count, and indicating explainability for pathologic judgements. Several models predict outcomes beyond pathologic diagnosis and predict clinical outcomes like patients' survival and molecular alterations. The manuscript emphasizes the potential of AI to enhance accuracy and efficiency in pathology, while also addressing the challenges and future directions for integrating AI into clinical practice.</p>","PeriodicalId":7305,"journal":{"name":"Advances In Anatomic Pathology","volume":" ","pages":"344-351"},"PeriodicalIF":5.1000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances In Anatomic Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/PAP.0000000000000448","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PATHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This manuscript provides a comprehensive overview of the application of artificial intelligence (AI) in lung pathology, particularly in the diagnosis of lung cancer. It discusses various AI models designed to support pathologists and clinicians. AI models supporting pathologists are to standardize diagnosis, score PD-L1 status, supporting tumor cellularity count, and indicating explainability for pathologic judgements. Several models predict outcomes beyond pathologic diagnosis and predict clinical outcomes like patients' survival and molecular alterations. The manuscript emphasizes the potential of AI to enhance accuracy and efficiency in pathology, while also addressing the challenges and future directions for integrating AI into clinical practice.
期刊介绍：
Advances in Anatomic Pathology provides targeted coverage of the key developments in anatomic and surgical pathology. It covers subjects ranging from basic morphology to the most advanced molecular biology techniques. The journal selects and efficiently communicates the most important information from recent world literature and offers invaluable assistance in managing the increasing flow of information in pathology.
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