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Automated diagnosis and treatment planning in dentistry

Bibliographic Data

ID15799673
AuthorsSalman Aziz (0000-0003-3266-105X, National University of Medical Sciences, corresponding author), Kashif Adnan (0009-0006-1858-3605, Royal College of Physicians and Surgeons of Glasgow), Hijab Fatemah (Sir Syed University of Engineering and Technology), Umair Farrukh (Rawalpindi Medical University), Ehsan Rathore (Farooq Hospital), Muhammad Umer (0000-0001-9334-3261)
Year2023
Volume7
IssueS1
Pages1166-1179
Publication date2023-06-07
Open AccessYes
TypeARTICLE
VenueInternational Journal of Health Sciences (JOURNAL)
Journal identifiersISSN: 2550-696X • E-ISSN: 2550-6978
PublisherUniversidad Tecnica de Manabi (PUBLISHER • EC)
DOI10.53730/ijhs.v7ns1.14330
OpenAlexW4379802411
LanguageEN

This study aims to investigate the perceptions and experiences regarding automated diagnosis and treatment planning in dentistry. The field of automated diagnosis and treatment planning is rapidly evolving, leveraging advanced technologies such as artificial intelligence (AI) and machine learning to enhance patient care and outcomes. However, there is a need to understand the perspectives of dental professionals regarding the adoption and implementation of these automated systems. A questionnaire survey was conducted among 100 dentists from various dental practices to gather data on their familiarity, usage, and perceptions of automated diagnosis and treatment planning. The survey also explored the perceived benefits, challenges, and future implications of automated systems in dental care. Preliminary findings indicate that the majority of dentists in the sample (80%) have some level of familiarity with automated diagnosis and treatment planning. However, only 45% reported actively using such systems in their practice. Among the dentists using automated systems, the most commonly cited benefits include time-saving (60%), enhanced accuracy (55%), and improved treatment planning (50%). Challenges associated with the adoption of automated systems were also identified

Perception · Radiation treatment planning · Dental Implant Techniques and Outcomes · Dental Radiography and Imaging · Dental Research and COVID-19 · Medicine · Psychology

Highly citedNo

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