Machine Learning Algorithms as a Computer-Assisted Decision Tool for Oral Cancer Prognosis and Management Decisions: A Systematic Review.

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Abstract

Despite multiple prognostic indicators described for oral cavity squamous cell carcinoma (OCSCC), its management still continues to be a matter of debate. Machine learning is a subset of artificial intelligence that enables computers to learn from historical data, gather insights, and make predictions about new data using the model learned. Therefore, it can be a potential tool in the field of head and neck cancer.

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Author and article information

Journal

Journal ID (iso-abbrev): ORL J Otorhinolaryngol Relat Spec

Title: ORL; journal for oto-rhino-laryngology and its related specialties

Publisher: S. Karger AG

ISSN (Electronic): 1423-0275

ISSN (Print): 0301-1569

Publication date (Electronic): 2022

Volume: 84

Issue: 4

Affiliations

[1 ] Otorhinolaryngology - Head & Neck Surgery Department, Hospital Universitario Donostia, Biodonostia Health Research Institute, San Sebastian, Spain.

[2 ] Head & Neck Study Group of Young-Otolaryngologists of the International Federations of Oto-Rhino-Laryngological Societies (YO-IFOS), San Sebastian, Spain.

[3 ] Computational Intelligence Group, Facultad de Informatica UPV/EHU, San Sebastian, Spain.

[4 ] LEGIT Health, Bilbao, Spain.

[5 ] Department of Human Anatomy & Experimental Oncology, University of Mons, Mons, Belgium.

[6 ] Department of Otolaryngology - Hospital Complex of Santiago de Compostela, Santiago de Compostela, Spain.

[7 ] Otorhinolaryngology - Head and Neck Surgery Department, Complexo Hospitalario Universitario A Coruña (CHUAC), A Coruña, Spain.

[8 ] Maxillofacial Surgery Unit, University Hospital of Sassari, Sassari, Italy.

[9 ] Department of Otorhinolaryngology - Head and Neck Surgery, University of Brescia, Brescia, Italy.

[10 ] Department of Otolaryngology-Head & Neck Surgery, Morgagni Pierantoni Hospital, Forli, Italy.

[11 ] Division of Otolaryngology-Head & Neck Surgery, Centre Hospitalier de l'Université de Montréal, Montreal, Québec, Canada.

[12 ] Division of Otolaryngology, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa.

Article

Publisher Item ID: 000520672

DOI: 10.1159/000520672

PubMed ID: 35021182

SO-VID: 750fd50d-ab4c-4ca5-bb16-d839efad4e6c

History

Keywords: Management,Prognosis,Cancer,Machine learning,Oral cavity

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Keywords: Management, Prognosis, Cancer, Machine learning, Oral cavity

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