The Intersection Between Neuropathology and Artificial Intelligence: A Review.
Artificial intelligence (AI) has become increasingly relevant in computational pathology, with expanding applications in neuropathology and neuro-oncology. To provide an overview of the main applications of AI in the evaluation of central nervous system tumors, focusing on diagnostic, prognostic, an...
| Publicado en: | Sage Open Pathology Vol. 19; pp. 1 - 12 |
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| Autor principal: | |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
8/11/2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=196123417&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 196123417 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 30502098 NYAB jtl: Sage Open Pathology issn: 30502098 maglogo: N pubinfo: dt: 8/11/2026 vid: 19 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 196123417 196123417 196123417 10.1177/30502098261472442 196123417 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: The Intersection Between Neuropathology and Artificial Intelligence: A Review. aug: au: Frassetto, Fernando Pereira affil: Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo, São Paulo, Brazil sug: subj: Artificial Intelligence Neurology Pathology Central Nervous System Neoplasms Diagnosis Central Nervous System Neoplasms Prognosis Health Care Delivery, Integrated Neoplasms Classification Machine Learning Deep Learning Multiomics Natural Language Processing Digital Health ab: Artificial intelligence (AI) has become increasingly relevant in computational pathology, with expanding applications in neuropathology and neuro-oncology. To provide an overview of the main applications of AI in the evaluation of central nervous system tumors, focusing on diagnostic, prognostic, and integrative approaches, a structured literature search was performed in PubMed, Web of Science, and Scopus, including studies published between 2006 and 2025 that addressed the use of AI in neuropathology and neuro-oncology. AI models have been applied to multiple tasks, including intraoperative diagnosis, tumor classification, prediction of molecular alterations, and integration of multi-omics data. Deep learning approaches, particularly convolutional neural networks and multimodal models, demonstrated high accuracy in several studies. In addition, emerging approaches such as foundation models and large language models have further expanded the scope of AI applications in neuropathology. In conclusion, AI shows significant potential to improve diagnostic accuracy, prognostic assessment, and personalized treatment in neuro-oncology. However, challenges such as data heterogeneity, lack of external validation, and barriers to clinical implementation remain. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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