AIMC Topic: Mouth Diseases

Clear Filters Showing 1 to 10 of 13 articles

Can deepseek and ChatGPT be used in the diagnosis of oral pathologies?

BMC oral health
OBJECTIVE: Artificial intelligence (AI) has been widely used in various medical fields to support diagnostic development. The development of different AI techniques has made important contributions to early diagnoses. This research compares and evalu...

Assessing the performance of an artificial intelligence based chatbot in the differential diagnosis of oral mucosal lesions: clinical validation study.

Clinical oral investigations
OBJECTIVES: Artificial intelligence (AI) is becoming more popular in medicine. The current study aims to investigate, primarily, if an AI-based chatbot, such as ChatGPT, could be a valid tool for assisting in establishing a differential diagnosis of ...

AI in oral medicine: is the future already here? A literature review.

British dental journal
Objective Artificial intelligence (AI) is reshaping many healthcare disciplines, mainly with newly developed computer systems or machines that have the ability to mimic human intelligence. This paper aims to review the available evidence on the appli...

Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model.

International dental journal
OBJECTIVES: Several factors such as unavailability of specialists, dental phobia, and financial difficulties may lead to a delay between receiving an oral radiology report and consulting a dentist. The primary aim of this study was to distinguish bet...

The innovation of AI-based software in oral diseases: clinical-histopathological correlation diagnostic accuracy primary study.

BMC oral health
BACKGROUND: Machine learning (ML) through artificial intelligence (AI) could provide clinicians and oral pathologists to advance diagnostic problems in the field of potentially malignant lesions, oral cancer, periodontal diseases, salivary gland dise...

Oral mucosal disease recognition based on dynamic self-attention and feature discriminant loss.

Oral diseases
OBJECTIVES: To develop a dynamic self-attention and feature discrimination loss function (DSDF) model for identifying oral mucosal diseases presented to solve the problems of data imbalance, complex image background, and high similarity and differenc...

Artificial Intelligence in Diagnosis of Oral Diseases: A Systematic Review.

The journal of contemporary dental practice
AIM: To understand the role of Artificial intelligence (AI) in oral radiology and its applications.

NFR-EDL: Non-linear fuzzy rank-based ensemble deep learning for accurate diagnosis of oral and dental diseases using RGB color photography.

Computers in biology and medicine
BACKGROUND: Oral health plays a vital role in our daily lives, affecting essential activities like eating, speaking, and smiling. Poor oral health can lead to significant social, psychological, and physical consequences, which makes early and accurat...