The Eye of Horus: Enhancing Head and Neck Cancer Care with Computer Vision.
Background: Head and neck cancer (HNC) poses formidable treatment challenges globally due to complex anatomy, image interpretation difficulties, and other obstacles, despite extensive research. Recent advancements in artificial intelligence (AI), particularly computer vision (CV), have demonstrated...
| Publicado en: | Oral Diseases Vol. 31; no. 12; pp. 3244 - 3253 |
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| Autores principales: | , , , , , , , , |
| Formato: | pictorial review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Dec2025
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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=192288904&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 192288904 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1354523X DZP jtl: Oral Diseases issn: 1354523X maglogo: Y pubinfo: dt: Dec2025 vid: 31 iid: 12 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 192288904 186180934 192288904 192288904 10.1111/odi.70013 192288904 ppf: 3244 ppct: 9 formats: tig: atl: The Eye of Horus: Enhancing Head and Neck Cancer Care with Computer Vision. aug: au: Shen, Ke‐Ru Cao, Lei‐Ming Li, Zi‐Zhan Wang, Guang‐Rui Xiao, Yao Luo, Han‐Yue Liu, Bing Xi, Lei Bu, Lin‐Lin affil: State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University, Wuhan, China sug: subj: Head and Neck Neoplasms Diagnosis Head and Neck Neoplasms Therapy Artificial Intelligence Utilization Health Personnel Psychosocial Factors Algorithms Utilization Engineering Disease Progression Deep Learning Tomography, X-Ray Computed Magnetic Resonance Imaging Endoscopy Workflow Quality Control (Technology) Neural Networks (Computer) Imaging, Three-Dimensional Augmented Reality Radiomics Radiotherapy Head and Neck Neoplasms Prognosis Health Care Delivery ab: Background: Head and neck cancer (HNC) poses formidable treatment challenges globally due to complex anatomy, image interpretation difficulties, and other obstacles, despite extensive research. Recent advancements in artificial intelligence (AI), particularly computer vision (CV), have demonstrated substantial potential in improving HNC management, yielding notable progress. Methods: We conducted a narrative review through massive literature research to explore the applications of CV in HNC and try to discuss its advantages as well as disadvantages through comparison. Results: We summarize the applications and cutting‐edge advances of CV in prevention, diagnosis, treatment, and prognosis prediction in HNC, synthesize the concepts and workflow of CV and discuss the advantages and disadvantages of it. Additionally, we bridge the gap among healthcare professionals and AI researchers to promote the development of relevant fields jointly. Conclusions: CV holds great promise in HNC. We should continually deepen cooperation and exchanges among healthcare professionals and AI researchers, thereby fostering the continuous development of CV in the treatment of HNC. With the continuous optimization of algorithms, the application of CV in HNC will become even more extensive. pubtype: Academic Journal doctype: pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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