ArticleBMC oral health2025
Artificial intelligence-based chatbot assistance in clinical decision-making for medically complex patients in oral surgery: a comparative study.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Artificial Intelligence in Oral and Maxillofacial Surgery-A Narrative Review.Journal of clinical medicine · 2026Review
- Performance Comparison of a Domain-Specific Chatbot and General-Purpose Chatbots in Dental Traumatology.Dental traumatology : official publication of International Association for Dental Traumatology · 2026Article
- Comparison of artificial intelligence-based chatbots and expert periodontists in responding to patient questions: a multi-dimensional analysis.BMC oral health · 2026Article
- Performance of ChatGPT in dental implant treatment planning: evaluation using the modified DISCERN, Global Quality Score, and accuracy-safety score.BMC oral health · 2026Article
- Performance of GPT-5, DeepSeek, and Claude in dental MCQs for medically compromised patients.Journal of translational medicine · 2026Article
- Artificial intelligence analysis of minimally invasive surgery data.Journal of robotic surgery · 2026Review
- Artificial Intelligence in Oral and Maxillofacial Surgery: Integrating Clinical Innovation and Workflow Optimization.Journal of clinical medicine · 2026Review
- Clinical Variables Associated with Physician-Driven Inclusion in a Special Management Program for Complex Patients.Journal of clinical medicine · 2025Article
- Development of a Conversational Artificial Intelligence-Based Web Application for Medical Consultations: Prototype Study.JMIRx med · 2025Article
- Comparative study of technical and patient-related question answering quality of DeepSeek-R1 and ChatGPT-4o in the field of oral and maxillofacial surgery.Oral and maxillofacial surgery · 2025Article
- Evaluation of ChatGPT-4's performance on pediatric dentistry questions: accuracy and completeness analysis.BMC oral health · 2025Article
- Evaluation of deepseek, gemini, ChatGPT-4o, and perplexity in responding to salivary gland cancer.BMC oral health · 2025Article
- Readability of AI-Generated Patient Information Leaflets on Alzheimer's, Vascular Dementia, and Delirium.Cureus · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis study aims to evaluate the potential of AI-based chatbots in assisting with clinical decision-making in the management of medically complex patients in oral surgery. MATERIALS AND
methodsA team of oral and maxillofacial surgeons developed a pool of open-ended questions de novo. The validity of the questions was assessed using Lawshe's Content Validity Index. The questions, which focused on systemic diseases and common conditions that may raise concerns during oral surgery, were presented to ChatGPT 3.5 and Claude-instant in two separate sessions, spaced one week apart. Two experienced maxillofacial surgeons, blinded to the chatbots, assessed the responses for quality, accuracy, and completeness using a modified DISCERN tool and Likert scale. Intraclass correlation, Mann-Whitney U test, skewness, and kurtosis coefficients were employed to compare the performances of the chatbots.
resultsMost responses were high quality: 86% and 79.6% for ChatGPT, and 81.25% and 89% for Claude-instant in sessions 1 and 2, respectively. In terms of accuracy, ChatGPT had 92% and 93.4% of its responses rated as completely correct in sessions 1 and 2, respectively, while Claude-instant had 95.2% and 89%. For completeness, ChatGPT had 88.5% and 86.8% of its responses rated as adequate or comprehensive in sessions 1 and 2, respectively, while Claude-instant had 95.2% and 86%.
conclusionOngoing software developments and the increasing acceptance of chatbots among healthcare professionals hold promise that these tools can provide rapid solutions to the high demand for medical care, ease professionals' workload, reduce costs, and save time.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.