Artificial intelligence as an adjunctive tool in hand and wrist surgery: a review DOI Open Access

Said Dababneh,

Justine Colivas,

Nadine Dababneh

et al.

Artificial Intelligence Surgery, Journal Year: 2024, Volume and Issue: 4(3), P. 214 - 32

Published: Sept. 2, 2024

Artificial intelligence (AI) is currently utilized across numerous medical disciplines. Nevertheless, despite its promising advancements, AI’s integration in hand surgery remains early stages and has not yet been widely implemented, necessitating continued research to validate efficacy ensure safety. Therefore, this review aims provide an overview of the utilization AI surgery, emphasizing current application clinical practice, along with potential benefits associated challenges. A comprehensive literature search was conducted PubMed, Embase, Medline, Cochrane libraries, adhering Preferred reporting items for systematic reviews meta-analyses (PRISMA) guidelines. The focused on identifying articles related utilizing multiple relevant keywords. Each identified article assessed based title, abstract, full text. primary 1,228 articles; after inclusion/exclusion criteria manual bibliography included articles, a total 98 were covered review. wrist diagnostic, which includes fracture detection, carpal tunnel syndrome (CTS), avascular necrosis (AVN), osteoporosis screening. Other applications include residents’ training, patient-doctor communication, surgical assistance, outcome prediction. Consequently, very tool that though further necessary fully integrate it into practice.

Language: Английский

Effectiveness of AI-powered Chatbots in responding to orthopaedic postgraduate exam questions—an observational study DOI
Raju Vaishya, Karthikeyan P. Iyengar, Mohit Kumar Patralekh

et al.

International Orthopaedics, Journal Year: 2024, Volume and Issue: 48(8), P. 1963 - 1969

Published: April 15, 2024

Language: Английский

Citations

17
ChatGPT Earns American Board Certification in Hand Surgery DOI
Diane Ghanem,

Joseph E. Nassar,

Joseph El Bachour

et al.

Hand surgery & rehabilitation, Journal Year: 2024, Volume and Issue: 43(3), P. 101688 - 101688

Published: March 27, 2024

Language: Английский

Citations

14
Higher education assessment practice in the era of generative AI tools DOI Open Access
Bayode Ogunleye, Kudirat Ibilola Zakariyyah, Oluwaseun Ajao

et al.

Journal of Applied Learning & Teaching, Journal Year: 2024, Volume and Issue: 7(1)

Published: March 31, 2024

The higher education (HE) sector benefits every nation's economy and society at large. However, their contributions are challenged by advanced technologies like generative artificial intelligence (GenAI) tools. In this paper, we provide a comprehensive assessment of GenAI tools towards pedagogic practice and, subsequently, discuss the potential impacts. This study experimented using three instruments from data science, analytics, construction management disciplines. Our findings two-fold: first, revealed that exhibit subject knowledge, problem-solving, analytical, critical thinking, presentation skills thus can limit learning when used unethically. Secondly, design certain disciplines limitations Based on our findings, made recommendations how AI be utilised for teaching in HE.

Language: Английский

Citations

9
Performance of ChatGPT versus Google Bard on Answering Postgraduate-Level Surgical Examination Questions: A Meta-Analysis DOI
A Andrew, Sarah Zhao

Indian Journal of Surgery, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Language: Английский

Citations

1
Assessing the Feasibility of Using AI Models to Simplify Brain Imaging Reports for Patients: A Comparative Analysis of Four Large Language Models DOI
Min Xu, Yiwen Wang

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 396 - 406

Published: Jan. 1, 2025

Language: Английский

Citations

0
Accuracy of Large Language Models When Answering Clinical Research Questions: Systematic Review and Network Meta-Analysis DOI Creative Commons

Ling Wang,

Jinglin Li,

Boyang Zhuang

et al.

Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: 27, P. e64486 - e64486

Published: April 30, 2025

Large language models (LLMs) have flourished and gradually become an important research application direction in the medical field. However, due to high degree of specialization, complexity, specificity medicine, which results extremely accuracy requirements, controversy remains about whether LLMs can be used More studies evaluated performance various types but conclusions are inconsistent. This study uses a network meta-analysis (NMA) assess when answering clinical questions provide high-level evidence-based evidence for its future development In this systematic review NMA, we searched PubMed, Embase, Web Science, Scopus from inception until October 14, 2024. Studies on were included screened by reading published reports. The NMA conducted compare different questions, including objective open-ended top 1 diagnosis, 3 5 triage classification. was performed using Bayesian frequency theory methods. Indirect intercomparisons between programs grading scale. A larger surface under cumulative ranking curve (SUCRA) value indicates higher corresponding LLM accuracy. examined 168 articles encompassing 35,896 3063 cases. Of studies, 40 (23.8%) considered low risk bias, 128 (76.2%) had moderate risk, none rated as having risk. ChatGPT-4o (SUCRA=0.9207) demonstrated strong terms followed Aeyeconsult (SUCRA=0.9187) ChatGPT-4 (SUCRA=0.8087). (SUCRA=0.8708) excelled at questions. diagnosis cases, human experts (SUCRA=0.9001 SUCRA=0.7126, respectively) ranked highest, while Claude Opus (SUCRA=0.9672) well diagnosis. Gemini (SUCRA=0.9649) highest SUCRA area Our that has advantage For may more credible. Humans accurate performs better classification, is advantageous. analysis offers valuable insights clinicians practitioners, empowering them effectively leverage improved decision-making learning, management scenarios. PROSPERO CRD42024558245; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024558245.

Language: Английский

Citations

0
Comparison of Hand Surgery Certification Exams in Europe and the United States Using ChatGPT 4.0 DOI

Salman Hasan,

Kyros Ipaktchi, Nicolás Meyer

et al.

Journal of Hand and Microsurgery, Journal Year: 2025, Volume and Issue: unknown, P. 100258 - 100258

Published: May 1, 2025

Language: Английский

Citations

0
ChatGPT performance on radiation technologist and therapist entry to practice exams DOI Creative Commons
Ryan Duggan, Kaitlyn M. Tsuruda

Journal of medical imaging and radiation sciences, Journal Year: 2024, Volume and Issue: 55(4), P. 101426 - 101426

Published: May 25, 2024

BackgroundThe aim of this study was to describe the proficiency ChatGPT (GPT-4) on certification style exams from Canadian Association Medical Radiation Technologists (CAMRT), and its performance across multiple exam attempts.MethodsChatGPT prompted with questions CAMRT practice in disciplines radiological technology, magnetic resonance (MRI), nuclear medicine radiation therapy (87-98 each). attempted each five times. Exam evaluated using descriptive statistics, stratified by discipline question type (knowledge, application, critical thinking). Light's Kappa used assess agreement answers attempts.ResultsUsing a passing grade 65 %, passed technology only once (20 %), MRI all times (100 three (60 %). ChatGPT's best knowledge except therapy. It performed worst thinking questions. Agreement responses attempts substantial within MRI, medicine, almost perfect for therapy.ConclusionChatGPT able pass technologists therapists, but varied between disciplines. The algorithm demonstrated it provided attempts. Future research evaluating standardized tests should consider repeated measures.

Language: Английский

Citations

3
Opportunities and Challenges of Chatbots in Ophthalmology: A Narrative Review DOI Open Access
Mehmet Cem Sabaner, Rodrigo Anguita, Fares Antaki

et al.

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(12), P. 1165 - 1165

Published: Dec. 21, 2024

Artificial intelligence (AI) is becoming increasingly influential in ophthalmology, particularly through advancements machine learning, deep robotics, neural networks, and natural language processing (NLP). Among these, NLP-based chatbots are the most readily accessible driven by AI-based large models (LLMs). These have facilitated new research avenues gained traction both clinical surgical applications ophthalmology. They also being utilized studies on ophthalmology-related exams, those containing multiple-choice questions (MCQs). This narrative review evaluates opportunities challenges of integrating into ophthalmology research, with separate assessments involving open- close-ended questions. While demonstrated sufficient accuracy handling MCQ-based studies, supporting their use education, additional exam security measures necessary. The open-ended question responses suggests that LLM could be applied across nearly all areas shown promise for addressing patient inquiries, offering medical advice, triage, facilitating diagnosis differential diagnosis, aiding planning. However, ethical implications, confidentiality concerns, physician liability, issues surrounding privacy remain pressing challenges. Although AI has significant care, it currently effective as a supportive tool rather than replacement human physicians.

Language: Английский

Citations

3
Evolution of a Large Language Model for Preoperative Assessment Based on the Japanese Circulation Society 2022 Guideline on Perioperative Cardiovascular Assessment and Management for Non-Cardiac Surgery DOI Open Access
Takahiro Kamihara,

Masanori Tabuchi,

Takuya Omura

et al.

Circulation Reports, Journal Year: 2024, Volume and Issue: 6(4), P. 142 - 148

Published: March 14, 2024

The Japanese Circulation Society 2022 Guideline on Perioperative Cardiovascular Assessment and Management for Non-Cardiac Surgery standardizes preoperative cardiovascular assessments. present study investigated the efficacy of a large language model (LLM) in providing accurate responses meeting JCS Guideline.

Language: Английский

Citations

2