Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.

Journal: Pain research & management

PMID: 33986900

Abstract

PURPOSE: The study explored the clinical influence, effectiveness, limitations, and human comparison outcomes of machine learning in diagnosing (1) dental diseases, (2) periodontal diseases, (3) trauma and neuralgias, (4) cysts and tumors, (5) glandular disorders, and (6) bone and temporomandibular joint as possible causes of dental and orofacial pain.

Authors

Taseef Hasan Farook

Maxillofacial Prosthetic Service, Prosthodontic Unit, School of Dental Sciences, UniversitiSains Malaysia, Health Campus, Kelantan 16150, Malaysia.
Nafij Bin Jamayet

Division of Clinical Dentistry (Prosthodontics), School of Dentistry, International Medical University, Kuala Lumpur 57000, Malaysia.
Johari Yap Abdullah

Craniofacial Imaging Laboratory, School of Dental Sciences, Universiti Sains Malaysia, Health Campus, 16150 Kubang Kerian, Kota Bharu, Kelantan, Malaysia. johariyap@usm.my.
Mohammad Khursheed Alam

Department of Preventive Dentistry, College of Dentistry, Jouf University, Sakaka, Al Jouf, 72345, Saudi Arabia.

Keywords

Algorithms Artificial Intelligence Diagnostic Tests, Routine Facial Pain Humans Machine Learning Pain Management

External Resources

View on PubMed Access via DOI PubMed (33986900)

Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review.

Abstract

Authors

Keywords

External Resources

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