Computational and Structural Biotechnology Journal, Journal Year: 2024, Volume and Issue: 28, P. 9 - 15
Published: Dec. 26, 2024
Language: Английский
Journal of Prosthetic Dentistry, Journal Year: 2024, Volume and Issue: 131(4), P. 659.e1 - 659.e6
Published: Feb. 2, 2024
Language: Английский
Citations
27
Diagnostics, Journal Year: 2024, Volume and Issue: 14(8), P. 839 - 839
Published: April 18, 2024
In the evolving field of maxillofacial surgery, integrating advanced technologies like Large Language Models (LLMs) into medical practices, especially for trauma triage, presents a promising yet largely unexplored potential. This study aimed to evaluate feasibility using LLMs triaging complex cases by comparing their performance against expertise tertiary referral center.
Language: Английский
Citations
18
PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0317423 - e0317423
Published: Jan. 29, 2025
This study aims to evaluate the performance of latest large language models (LLMs) in answering dental multiple choice questions (MCQs), including both text-based and image-based questions. A total 1490 MCQs from two board review books for United States National Board Dental Examination were selected. evaluated six LLMs as August 2024, ChatGPT 4.0 omni (OpenAI), Gemini Advanced 1.5 Pro (Google), Copilot with GPT-4 Turbo (Microsoft), Claude 3.5 Sonnet (Anthropic), Mistral Large 2 (Mistral AI), Llama 3.1 405b (Meta). χ2 tests performed determine whether there significant differences percentages correct answers among sample each discipline (p < 0.05). Significant observed percentage accurate across questions, (p<0.001). For sample, (85.5%), (84.0%), (83.8%) demonstrated highest accuracy, followed by (78.3%) (77.1%), (72.4%) exhibiting lowest. Newer versions demonstrate superior compared earlier versions. Copilot, Claude, achieved high accuracy on low capable handling limited clinicians students should prioritize most up-to-date when supporting their learning, clinical practice, research.
Language: Английский
Citations
2
BDJ Open, Journal Year: 2024, Volume and Issue: 10(1)
Published: June 12, 2024
This study underscores the transformative role of Artificial Intelligence (AI) in healthcare, particularly promising applications Large Language Models (LLMs) delivery post-operative dental care. The aim is to evaluate performance an embedded GPT model and its comparison with ChatGPT-3.5 turbo. assessment focuses on aspects like response accuracy, clarity, relevance, up-to-date knowledge addressing patient concerns facilitating informed decision-making.
Language: Английский
Citations
9
Frontiers in Dental Medicine, Journal Year: 2025, Volume and Issue: 5
Published: Jan. 6, 2025
Artificial intelligence has dramatically reshaped our interaction with digital technologies, ushering in an era where advancements AI algorithms and Large Language Models (LLMs) have natural language processing (NLP) systems like ChatGPT. This study delves into the impact of cutting-edge LLMs, notably OpenAI's ChatGPT, on medical diagnostics, a keen focus dental sector. Leveraging publicly accessible datasets, these models augment diagnostic capabilities professionals, streamline communication between patients healthcare providers, enhance efficiency clinical procedures. The advent ChatGPT-4 is poised to make substantial inroads practices, especially realm oral surgery. paper sheds light current landscape explores potential future research directions burgeoning field offering valuable insights for both practitioners developers. Furthermore, it critically assesses broad implications challenges within various sectors, including academia healthcare, thus mapping out overview AI's role transforming diagnostics enhanced patient care.
Language: Английский
Citations
1
International Dental Journal, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
In the final part of this two article on artificial intelligence (AI) in dentistry we review its transformative role, focusing AI dental education, patient communications, challenges integration, strategies to overcome barriers, ethical considerations, and finally, recently released International Dental Federation (FDI) Communique (white paper) Dentistry. education is highlighted for potential enhancing theoretical practical dimensions, including telemonitoring virtual training ecosystems. Challenges integration are outlined, such as data availability, bias, human accountability. Strategies these include promoting literacy, establishing regulations, specific implementations. Ethical considerations within dentistry, privacy algorithm emphasized. The need clear guidelines ongoing evaluation systems crucial. FDI White Paper Dentistry provides insights into significance oral care, research, along with standards governance. It discusses AI's impact individual patients, community health, research. paper addresses biases, limited generalizability, accessibility, regulatory requirements practice. conclusion, plays a significant role modern offering benefits diagnosis, treatment planning, decision-making. While facing challenges, strategic initiatives targeted implementations can help barriers maximize dentistry. essential ensuring responsible, effective efficacious deployment technologies ecosystem.
Language: Английский
Citations
1
Dentomaxillofacial Radiology, Journal Year: 2024, Volume and Issue: 53(6), P. 390 - 395
Published: June 7, 2024
Abstract Objectives This study evaluated the performance of four large language model (LLM)-based chatbots by comparing their test results with those dental students on an oral and maxillofacial radiology examination. Methods ChatGPT, ChatGPT Plus, Bard, Bing Chat were tested 52 questions from regular college examinations. These categorized into three educational content areas: basic knowledge, imaging equipment, image interpretation. They also classified as multiple-choice (MCQs) short-answer (SAQs). The accuracy rates compared students, further analysis was conducted based question type. Results students’ overall rate 81.2%, while that varied: 50.0% for 65.4% 63.5% Chat. Plus achieved a higher knowledge than (93.8% vs. 78.7%). However, all performed poorly in interpretation, below 35.0%. All scored less 60.0% MCQs, but better SAQs. Conclusions unsatisfactory. Further training using specific, relevant data derived solely reliable sources is required. Additionally, validity these chatbots’ responses must be meticulously verified.
Language: Английский
Citations
6
Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 2, P. 100078 - 100078
Published: Feb. 27, 2024
The integration of AI-powered ChatGPT in oral and maxillofacial surgery marks a transformative shift healthcare, enhancing diagnostics, treatment planning, patient communication, surgical training. Its rapid analysis vast datasets ensures precise, personalized diagnoses strategies, minimizing risks improving outcomes. facilitates virtual consultations, educates patients, serves as real-time assistant during procedures, while AI-driven simulations refine the skills aspiring surgeons secure environment. Despite challenges like data privacy algorithm validation, ongoing research promises to bolster AI's role surgery. Overall, ChatGPT's incorporation reshapes surgery, promising heightened precision, efficiency, care quality, ultimately revolutionizing practices well-being.
Language: Английский
Citations
5
International Dental Journal, Journal Year: 2024, Volume and Issue: unknown
Published: Aug. 1, 2024
Given the increasing interest in using large language models (LLMs) for self-diagnosis, this study aimed to evaluate comprehensiveness of two prominent LLMs, ChatGPT-3.5 and ChatGPT-4, addressing common queries related gingival endodontic health across different contexts query types.
Language: Английский
Citations
5
Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(4), P. 1363 - 1363
Published: Feb. 18, 2025
Objectives: This review aimed to evaluate the role of ChatGPT in original research articles within field oral and maxillofacial surgery (OMS), focusing on its applications, limitations, future directions. Methods: A literature search was conducted PubMed using predefined terms Boolean operators identify utilizing published up October 2024. The selection process involved screening studies based their relevance OMS with 26 meeting final inclusion criteria. Results: has been applied various OMS-related domains, including clinical decision support real virtual scenarios, patient practitioner education, scientific writing referencing, ability answer licensing exam questions. As a tool, demonstrated moderate accuracy (approximately 70-80%). It showed high (up 90%) providing guidance information. However, reliability remains inconsistent across different necessitating further evaluation. Conclusions: While presents potential benefits OMS, particularly supporting decisions improving access medical information, it should not be regarded as substitute for clinicians must used an adjunct tool. Further validation technological refinements are required enhance effectiveness settings.
Language: Английский
Citations
0