Background: The aim of this cross-sectional observational analytical study was to assess the accuracy and consistency of responses provided by Google Gemini (GG), a free-access high-performance multimodal large language model, to questions related to the European Society of Endodontology position statement on the management of traumatized permanent teeth (MTPT).

Materials And Methods: Three academic endodontists developed a set of 99 yes/no questions covering all areas of the MTPT. Nine general dentists and 22 endodontic specialists evaluated these questions for clarity and comprehension through an iterative process. Two academic dental trauma experts categorized the knowledge required to answer each question into three levels. The three academic endodontists submitted the 99 questions to the GG, resulting in 297 responses, which were then assessed for accuracy and consistency. Accuracy was evaluated using the Wald binomial method, while the consistency of GG responses was assessed using the kappa-Fleiss coefficient with a confidence interval of 95%. A 5% significance level chi-squared test was used to evaluate the influence of question level of knowledge on accuracy and consistency.

Results: The responses generated by Gemini showed an overall moderate accuracy of 80.81%, with no significant differences found between the responses of the academic endodontists. Overall, high consistency (95.96%) was demonstrated, with no significant differences between GG responses across the three accounts. The analysis also revealed no correlation between question level of knowledge and accuracy or consistency, with no significant differences.

Conclusions: The results of this study could significantly impact the potential use of Gemini as a free-access source of information for clinicians in the MTPT.

Download full-text PDF

Source
http://dx.doi.org/10.1111/edt.13004DOI Listing

Publication Analysis

Top Keywords

accuracy consistency
16
academic endodontists
12
management traumatized
8
traumatized permanent
8
permanent teeth
8
consistency responses
8
gemini free-access
8
three academic
8
responses assessed
8
question level
8

Similar Publications

Background: The number of meniscal repairs being completed each year is increasing; however, the optimal, cost-effective postoperative assessment to determine the success or failure of a meniscal repair is not well known.

Purpose/hypothesis: The purpose of this systematic review was to identify the clinical examination testing that correlates with objective magnetic resonance imaging (MRI) or second-look arthroscopy (SLA) findings to determine an optimal clinical workup for assessing postoperative meniscal repair healing. It was hypothesized that specific clinical tests would correlate with meniscal repairs that did not heal.

View Article and Find Full Text PDF

During batch fermentation, a variety of compounds are synthesized, as microorganisms undergo distinct growth phases: lag, exponential, growth-no-growth transition, stationary, and decay. A detailed understanding of the metabolic pathways involved in these phases is crucial for optimizing the production of target compounds. Dynamic flux balance analysis (dFBA) offers insight into the dynamics of metabolic pathways.

View Article and Find Full Text PDF

As Water Sensitive Urban Design (WSUD) is a key strategy in integrated urban water management worldwide, there is a need for robust monitoring of WSUD systems. Being economical and flexible for operation and communication, low-cost sensor systems show great potential to mainstream digital water management. Yet, such systems are insufficiently tested, casting doubt on the reliability of their measurements.

View Article and Find Full Text PDF

Purpose: The integration of artificial intelligence (AI) into medical education has witnessed significant progress, particularly in the domain of language models. This study focuses on assessing the performance of two notable language models, ChatGPT and BingAI Precise, in answering the National Eligibility Entrance Test for Postgraduates (NEET-PG)-style practice questions, simulating medical exam formats.

Methods: A cross-sectional study conducted in June 2023 involved assessing ChatGPT and BingAI Precise using three sets of NEET-PG practice exams, comprising 200 questions each.

View Article and Find Full Text PDF

Comparative study of imputation strategies to improve the sarcopenia prediction task.

Digit Health

January 2025

Department of Exercise Rehabilitation & Welfare, Gachon University, Incheon, Republic of Korea.

Objective: Sarcopenia, a condition characterized by the progressive loss of skeletal muscle mass and strength, poses significant challenges in research due to missing data. Incomplete datasets undermine the accuracy and reliability of studies, necessitating effective imputation techniques. This study conducts a comparative analysis of three advanced methods-multiple imputation by chained equations (MICE), support vector regression, and K-nearest neighbors (KNN)-to address data completeness issues in sarcopenia research.

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!