AIMC Topic: Dental Implants

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Performance of two different artificial intelligence models in dental implant planning among four different implant planning software: a comparative study.

BMC oral health
BACKGROUND: The integration of artificial intelligence (AI) in dental implant planning has emerged as a transformative approach to enhance diagnostic accuracy and efficiency. This study aimed to evaluate the performance of two object detection models...

Comparison of responses from different artificial intelligence-powered chatbots regarding the All-on-four dental implant concept.

BMC oral health
BACKGROUND: Recent advancements in Artificial Intelligence (AI) have transformed the healthcare field, particularly through chatbots like ChatGPT, OpenEvidence, and MediSearch. These tools analyze complex data to aid clinical decision-making, enhanci...

Development and precision evaluation of a robotic system for oral implant surgery using personalized digital guides and optical spatial positioning technology.

PloS one
Oral implant surgery demands a high level of precision and expertise, making the integration of robotic assistance an optimal solution. This study introduces an innovative dental implant robotic system designed to enhance accuracy during cavity prepa...

Optimized classification of dental implants using convolutional neural networks and pre-trained models with preprocessed data.

BMC oral health
OBJECTIVE: This study evaluates the performance of various classifiers and pre-trained models for dental implant state classification using preprocessed radiography images with masks.

Evaluation of artificial intelligence robot's knowledge and reliability on dental implants and peri-implant phenotype.

Scientific reports
The aim of this study was to evaluate the reliability and quality of information generated by ChatGPT regarding dental implants and peri-implant phenotypes. A structured questionnaire on these topics was presented to the AI-based chatbot, and its res...

Progressive multi-task learning for fine-grained dental implant classification and segmentation in CBCT image.

Computers in biology and medicine
With the ongoing advancement of digital technology, oral medicine transitions from traditional diagnostics to computer-assisted diagnosis and treatment. Identifying dental implants in patients without records is complex and time-consuming. Accurate i...

Improving machine learning-based bitewing segmentation with synthetic data.

Journal of dentistry
OBJECTIVES: Class imbalance in datasets is one of the challenges of machine learning (ML) in medical image analysis. We employed synthetic data to overcome class imbalance when segmenting bitewing radiographs as an exemplary task for using ML.

Deep learning-based prediction of possibility for immediate implant placement using panoramic radiography.

Scientific reports
In this study, we investigated whether deep learning-based prediction of immediate implant placement is possible. Panoramic radiographs of 201 patients with 874 teeth (Group 1: 440 teeth difficult to place implant immediately after extraction, Group ...

Precise multi-factor immediate implant placement decision models based on machine learning.

Scientific reports
This study aims to explore the effect of implant apex design, osteotomy preparation, intraosseous depth and bone quality on immediate implant placement insertion torque and establish a more sophisticated decision model with multi-factor analysis base...

Optimizing dental implant identification using deep learning leveraging artificial data.

Scientific reports
This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using...