{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:08:27Z","timestamp":1784095707711,"version":"3.55.0"},"reference-count":86,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CIMB"],"abstract":"<jats:p>Exosomes are 30\u2013150 nm extracellular vesicles that convey molecular information reflecting the physiological and pathological states of their source cells. In precision oncology, they function as a non-invasive \u201cliquid biopsy,\u201d enabling real-time monitoring of tumor dynamics and metastasis. However, extreme biofluid heterogeneity poses significant challenges for their isolation and analysis using conventional statistical approaches. This review aims to examine how artificial intelligence (AI), specifically machine learning and deep learning, transforms complex exosomal \u201cnoise\u201d into actionable clinical insights. AI enhances exosome isolation, enables disease-specific biomarker identification, and predicts therapeutic responses with high precision. Integrating multi-omics data and single-exosome analysis enables AI-driven models to facilitate early cancer detection and therapeutic resistance monitoring. Despite challenges related to standardization and data privacy, the convergence of AI and exosome biology is poised to transform reactive cancer treatments into a proactive, personalized medical ecosystem. This approach also provides a framework for managing other complex systemic diseases.<\/jats:p>","DOI":"10.3390\/cimb48070704","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T13:16:28Z","timestamp":1783689388000},"page":"704","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence-Enabled Exosomes in Precision Oncology: A Framework for Clinical Utility and Biomedical Applications"],"prefix":"10.3390","volume":"48","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0658-4604","authenticated-orcid":false,"given":"Prakash","family":"Gangadaran","sequence":"first","affiliation":[{"name":"Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea"},{"name":"Cardiovascular Research Institute, Kyungpook National University, Daegu 41944, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6987-0854","authenticated-orcid":false,"given":"Ramya Lakshmi","family":"Rajendran","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea"},{"name":"Cardiovascular Research Institute, Kyungpook National University, Daegu 41944, Republic of Korea"},{"name":"BK21 FOUR KNU Convergence Educational Program of Biomedical Sciences for Creative Future Talents, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1676-561X","authenticated-orcid":false,"given":"Muthu Subash","family":"Kavitha","sequence":"additional","affiliation":[{"name":"School of Information and Data Sciences, Nagasaki University, Nagasaki 852-8521, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7700-3929","authenticated-orcid":false,"given":"Byeong-Cheol","family":"Ahn","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea"},{"name":"Cardiovascular Research Institute, Kyungpook National University, Daegu 41944, Republic of Korea"},{"name":"Department of Nuclear Medicine, Kyungpook National University Hospital, Daegu 41944, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1146\/annurev-cellbio-101512-122326","article-title":"Biogenesis, Secretion, and Intercellular Interactions of Exosomes and Other Extracellular Vesicles","volume":"30","author":"Colombo","year":"2014","journal-title":"Annu. 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