Vanesa García-Barberán, María Elena Gómez Del Pulgar, Heidy M Guamán, Alberto Benito-Martin
{"title":"The times they are AI-changing: AI-powered advances in the application of extracellular vesicles to liquid biopsy in breast cancer.","authors":"Vanesa García-Barberán, María Elena Gómez Del Pulgar, Heidy M Guamán, Alberto Benito-Martin","doi":"10.20517/evcna.2024.51","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) is revolutionizing scientific research by facilitating a paradigm shift in data analysis and discovery. This transformation is characterized by a fundamental change in scientific methods and concepts due to AI's ability to process vast datasets with unprecedented speed and accuracy. In breast cancer research, AI aids in early detection, prognosis, and personalized treatment strategies. Liquid biopsy, a noninvasive tool for detecting circulating tumor traits, could ideally benefit from AI's analytical capabilities, enhancing the detection of minimal residual disease and improving treatment monitoring. Extracellular vesicles (EVs), which are key elements in cell communication and cancer progression, could be analyzed with AI to identify disease-specific biomarkers. AI combined with EV analysis promises an enhancement in diagnosis precision, aiding in early detection and treatment monitoring. Studies show that AI can differentiate cancer types and predict drug efficacy, exemplifying its potential in personalized medicine. Overall, the integration of AI in biomedical research and clinical practice promises significant changes and advancements in diagnostics, personalized medicine-based approaches, and our understanding of complex diseases like cancer.</p>","PeriodicalId":520322,"journal":{"name":"Extracellular vesicles and circulating nucleic acids","volume":"6 1","pages":"128-140"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11977355/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Extracellular vesicles and circulating nucleic acids","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20517/evcna.2024.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is revolutionizing scientific research by facilitating a paradigm shift in data analysis and discovery. This transformation is characterized by a fundamental change in scientific methods and concepts due to AI's ability to process vast datasets with unprecedented speed and accuracy. In breast cancer research, AI aids in early detection, prognosis, and personalized treatment strategies. Liquid biopsy, a noninvasive tool for detecting circulating tumor traits, could ideally benefit from AI's analytical capabilities, enhancing the detection of minimal residual disease and improving treatment monitoring. Extracellular vesicles (EVs), which are key elements in cell communication and cancer progression, could be analyzed with AI to identify disease-specific biomarkers. AI combined with EV analysis promises an enhancement in diagnosis precision, aiding in early detection and treatment monitoring. Studies show that AI can differentiate cancer types and predict drug efficacy, exemplifying its potential in personalized medicine. Overall, the integration of AI in biomedical research and clinical practice promises significant changes and advancements in diagnostics, personalized medicine-based approaches, and our understanding of complex diseases like cancer.