Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine.
The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Althoug...
| Publicado en: | Current Oncology Vol. 30; no. 3; pp. 2673 - 2702 |
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| Autores principales: | , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
MDPI
Mar2023
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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=162747170&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162747170 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11980052 5EKK jtl: Current Oncology issn: 11980052 maglogo: N pubinfo: dt: Mar2023 vid: 30 iid: 3 pid: 97109 pub: MDPI artinfo: ui: 162747170 10.3390/curroncol30030203 162747170 ppf: 2673 ppct: 29 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial Intelligence in Brain Tumor Imaging: A Step toward Personalized Medicine. aug: au: Cè, Maurizio Irmici, Giovanni Foschini, Chiara Danesini, Giulia Maria Falsitta, Lydia Viviana Serio, Maria Lina Fontana, Andrea Martinenghi, Carlo Oliva, Giancarlo Cellina, Michaela affil: Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono 7, 20122 Milan, Italy sug: ab: The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-tailored brain tumor management, achieving optimal onco-functional balance for each individual. AI-based models can positively impact different stages of the diagnostic and therapeutic process. Although the histological investigation will remain difficult to replace, in the near future the radiomic approach will allow a complementary, repeatable and non-invasive characterization of the lesion, assisting oncologists and neurosurgeons in selecting the best therapeutic option and the correct molecular target in chemotherapy. AI-driven tools are already playing an important role in surgical planning, delimiting the extent of the lesion (segmentation) and its relationships with the brain structures, thus allowing precision brain surgery as radical as reasonably acceptable to preserve the quality of life. Finally, AI-assisted models allow the prediction of complications, recurrences and therapeutic response, suggesting the most appropriate follow-up. Looking to the future, AI-powered models promise to integrate biochemical and clinical data to stratify risk and direct patients to personalized screening protocols. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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