人工智能在胰腺癌组织病理学和诊断中的应用——对临床决策和生物标志物发现的影响？

IF 2.2 4区生物学 Q3 CELL BIOLOGY

Cell Division Pub Date : 2025-06-17 DOI:10.1186/s13008-025-00158-w

Petra Weselá, Michal Eid, Petr Moravčík, Jakub Vlažný, Jan Hlavsa, Vladimír Procházka, Zdeněk Kala, Petr Vaňhara

{"title":"人工智能在胰腺癌组织病理学和诊断中的应用——对临床决策和生物标志物发现的影响？","authors":"Petra Weselá, Michal Eid, Petr Moravčík, Jakub Vlažný, Jan Hlavsa, Vladimír Procházka, Zdeněk Kala, Petr Vaňhara","doi":"10.1186/s13008-025-00158-w","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) and machine learning (ML) are rapidly advancing fields within computer science, driving significant progress in cancer diagnostics. Various ML models have been developed to assist diagnosis, guide therapy decisions, and facilitate early disease detection. In this review, we discuss diverse AI and ML approaches and critically evaluate their applications and limitations in pancreatic cancer histopathology, diagnostics, and biomarker discovery.","PeriodicalId":49263,"journal":{"name":"Cell Division","volume":"20 1","pages":"15"},"PeriodicalIF":2.2000,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12175320/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in pancreatic cancer histopathology and diagnostics - implications for clinical decisions and biomarker discovery?\",\"authors\":\"Petra Weselá, Michal Eid, Petr Moravčík, Jakub Vlažný, Jan Hlavsa, Vladimír Procházka, Zdeněk Kala, Petr Vaňhara\",\"doi\":\"10.1186/s13008-025-00158-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial intelligence (AI) and machine learning (ML) are rapidly advancing fields within computer science, driving significant progress in cancer diagnostics. Various ML models have been developed to assist diagnosis, guide therapy decisions, and facilitate early disease detection. In this review, we discuss diverse AI and ML approaches and critically evaluate their applications and limitations in pancreatic cancer histopathology, diagnostics, and biomarker discovery.\",\"PeriodicalId\":49263,\"journal\":{\"name\":\"Cell Division\",\"volume\":\"20 1\",\"pages\":\"15\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12175320/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell Division\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13008-025-00158-w\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Division","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13008-025-00158-w","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CELL BIOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

人工智能（AI）和机器学习（ML）是计算机科学领域的快速发展，推动了癌症诊断的重大进展。各种ML模型已经开发出来，以协助诊断，指导治疗决策，并促进早期疾病检测。在这篇综述中，我们讨论了不同的人工智能和机器学习方法，并批判性地评估了它们在胰腺癌组织病理学、诊断和生物标志物发现方面的应用和局限性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Artificial intelligence in pancreatic cancer histopathology and diagnostics - implications for clinical decisions and biomarker discovery?

查看原文本刊更多论文

Artificial intelligence in pancreatic cancer histopathology and diagnostics - implications for clinical decisions and biomarker discovery?

Artificial intelligence (AI) and machine learning (ML) are rapidly advancing fields within computer science, driving significant progress in cancer diagnostics. Various ML models have been developed to assist diagnosis, guide therapy decisions, and facilitate early disease detection. In this review, we discuss diverse AI and ML approaches and critically evaluate their applications and limitations in pancreatic cancer histopathology, diagnostics, and biomarker discovery.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Cell Division CELL BIOLOGY-

CiteScore

3.70

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Cell Division is an open access, peer-reviewed journal that encompasses all the molecular aspects of cell cycle control and cancer, cell growth, proliferation, survival, differentiation, signalling, gene transcription, protein synthesis, genome integrity, chromosome stability, centrosome duplication, DNA damage and DNA repair. Cell Division provides an online forum for the cell-cycle community that aims to publish articles on all exciting aspects of cell-cycle research and to bridge the gap between models of cell cycle regulation, development, and cancer biology. This forum is driven by specialized and timely research articles, reviews and commentaries focused on this fast moving field, providing an invaluable tool for cell-cycle biologists. Cell Division publishes articles in areas which includes, but not limited to: DNA replication, cell fate decisions, cell cycle & development Cell proliferation, mitosis, spindle assembly checkpoint, ubiquitin mediated degradation DNA damage & repair Apoptosis & cell death