Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions.
Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, an...
| Publicado en: | Current Oncology Vol. 31; no. 9; pp. 5255 - 5291 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
MDPI
Sep2024
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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=179965634&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179965634 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11980052 5EKK jtl: Current Oncology issn: 11980052 maglogo: N pubinfo: dt: Sep2024 vid: 31 iid: 9 pid: 97109 pub: MDPI artinfo: ui: 179965634 10.3390/curroncol31090389 179965634 ppf: 5255 ppct: 36 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions. aug: au: Pham, Tuan D. Teh, Muy-Teck Chatzopoulou, Domniki Holmes, Simon Coulthard, Paul affil: Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Turner Street, London E1 2AD, UK sug: ab: Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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