Artificial intelligence (AI) is emerging as a transformative technology in healthcare, including endodontics. A gap in knowledge exists in understanding AI's applications and limitations among endodontic experts. This comprehensive review aims to (A) elaborate on technical and ethical aspects of using data to implement AI models in endodontics; (B) elaborate on evaluation metrics; (C) review the current applications of AI in endodontics; and (D) review the limitations and barriers to real-world implementation of AI in the field of endodontics and its future potentials/directions. The article shows that AI techniques have been applied in endodontics for critical tasks such as detection of radiolucent lesions, analysis of root canal morphology, prediction of treatment outcome and post-operative pain and more. Deep learning models like convolutional neural networks demonstrate high accuracy in these applications. However, challenges remain regarding model interpretability, generalizability, and adoption into clinical practice. When thoughtfully implemented, AI has great potential to aid with diagnostics, treatment planning, clinical interventions, and education in the field of endodontics. However, concerted efforts are still needed to address limitations and to facilitate integration into clinical workflows.

Download full-text PDF

Source
http://dx.doi.org/10.1111/iej.14128DOI Listing

Publication Analysis

Top Keywords

artificial intelligence
8
field endodontics
8
endodontics
7
intelligence endodontics
4
endodontics data
4
data preparation
4
clinical
4
preparation clinical
4
applications
4
clinical applications
4

Similar Publications

Preoperative surgical planning MRI for fibroids: What the surgeon needs to know and what to report.

J Med Imaging Radiat Oncol

December 2024

St John of God Subiaco, Perth, Western Australia, Australia.

Uterine leiomyomata, commonly known as fibroids, are prevalent benign tumours affecting a significant percentage of women of reproductive age. Although many patients remain asymptomatic, a substantial proportion experience severe symptoms, including abnormal uterine bleeding and adverse reproductive outcomes. Surgical intervention often becomes necessary for patients with symptomatic fibroids, despite advancements in medical therapies.

View Article and Find Full Text PDF

Background: In recent years, the adoption of large language model (LLM) applications, such as ChatGPT, has seen a significant surge, particularly among students. These artificial intelligence-driven tools offer unprecedented access to information and conversational assistance, which is reshaping the way students engage with academic content and manage the learning process. Despite the growing prevalence of LLMs and reliance on these technologies, there remains a notable gap in qualitative in-depth research examining the emotional and psychological effects of LLMs on users' mental well-being.

View Article and Find Full Text PDF

Reliability of generative artificial intelligence in identifying the major risk factors for venous thrombosis.

Blood Coagul Fibrinolysis

October 2024

Department of Haematology, Institute of Clinical Pathology and Medical Research (ICPMR), Sydney Centres for Thrombosis and Haemostasis, Westmead Hospital, Westmead.

View Article and Find Full Text PDF

Cortical lesions impact cognitive decline in multiple sclerosis via volume loss of nonlesional cortex.

Ann Clin Transl Neurol

December 2024

MS Center Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Objective: To assess the interrelationship between cortical lesions and cortical thinning and volume loss in people with multiple sclerosis within cortical networks, and how this relates to future cognition.

Methods: In this longitudinal study, 230 people with multiple sclerosis and 60 healthy controls underwent 3 Tesla MRI at baseline and neuropsychological assessment at baseline and 5-year follow-up. Cortical regions (N = 212) were divided into seven functional networks.

View Article and Find Full Text PDF

Increasing Reachability in Robotic Ultrasound Through Base Placement and Tool Design.

Int J Med Robot

February 2025

Insitute for Robotics and Kognitive Systems, University of Luebeck, Luebeck, Germany.

Background: Robotic ultrasound visualises internal organs in real-time for various medical applications without the harm of X-rays. The ultrasound probe is attached to the robot's end effector using custom-developed probe holders. This paper analyzes the impact of different probe holder geometries on the robot's base placement and reachability.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!