Petra Weselá, Michal Eid, Petr Moravčík, Jakub Vlažný, Jan Hlavsa, Vladimír Procházka, Zdeněk Kala, Petr Vaňhara
{"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":"<p><p>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.</p>","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}
引用次数: 0
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.
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