Nick Tarazona, MD’s Post

👉🏼 Performance of ChatGPT on Solving Orthopedic Board-Style Questions: A Comparative Analysis of ChatGPT 3.5 and ChatGPT 4 🤓 Sung Eun Kim 👇🏻 https://lnkd.in/eXCpfBgQ 🔍 Focus on data insights: - 📊 ChatGPT 3.5 achieved a correct answer rate of 37.5%, while ChatGPT 4 improved this significantly to 60.0%. - 🔍 The study analyzed 160 orthopedic board-style questions, categorized into 11 subcategories, highlighting the models' performance across different topics. - ⚖️ Inconsistency rates were notably high for ChatGPT 3.5 at 47.5%, compared to just 9.4% for ChatGPT 4, indicating improved reliability in the latter. 💡 Main outcomes and implications: - 🏆 ChatGPT 4 demonstrated superior accuracy, suggesting its potential utility in educational settings for medical training. - ⚠️ Despite improvements, the presence of misleading explanations and inconsistencies necessitates careful consideration before clinical application. - 📚 The findings underscore the importance of ongoing evaluation of AI tools in medicine to ensure their safe and effective use. 📚 Field significance: - 🌐 The research contributes to the growing body of evidence regarding the role of artificial intelligence in medical education and practice. - 🔬 It highlights the need for further studies to refine AI models for better accuracy and consistency in medical contexts. - 🧠 The results may influence how educators integrate AI tools into curricula, emphasizing the balance between technology and traditional learning methods. 🗄️: [#artificialintelligence #ChatGPT #orthopedics #medicaleducation #AIinmedicine #accuracy #inconsistency #clinicalapplication]

👉🏼 Assessment of ChatGPT generated educational material for head and neck surgery counseling 🤓 Lana Mnajjed 👇🏻 https://lnkd.in/e8Rm_nkn 🔍 Focus on data insights: - 📊 ChatGPT provided comprehensive responses for common perioperative counseling points. - ❓ Accuracy decreased when addressing surgical complications, indicating a gap in information. - 🌐 Compared to existing online educational materials, ChatGPT's responses scored at or above median levels for quality. 💡 Main outcomes and implications: - 🏥 ChatGPT can serve as a valuable tool for basic patient education in surgical contexts. - ⚠️ Caution is advised when relying on AI for detailed information on surgical complications. - 📈 The findings suggest potential for integrating AI tools in patient counseling, enhancing accessibility to information. 📚 Field significance: - 🔍 Highlights the need for ongoing evaluation of AI-generated content in medical education. - 💬 Encourages further research into improving AI accuracy in complex medical topics. - 🧑⚕️ Supports the integration of technology in healthcare communication strategies. 🗄️: [#ChatGPT #PatientCounseling #SurgicalEducation #AIinHealthcare #MedicalCommunication #PerioperativeCare]

AI Chatbots are promising patient info source for Glaucoma #AIChatbots 🤝 Download 1 Million Logo Prompt Generator 🔜 https://wapia.in/1mlogo 🤝 Follow us on Whatsapp 🔜 https://wapia.in/wabeta _ ❇️ Summary: A study led by Natasha N. Kolomeyer, MD, evaluated the responses of AI chatbots including ChatGPT, Bing, and Bard in answering glaucoma-related patient questions. The accuracy of AI chatbot responses was slightly below that of American Academy of Ophthalmology (AAO) patient education brochures. ChatGPT demonstrated the most comprehensive responses, while Bing had the lowest word and character counts. The study suggests that AI chatbots can be a useful supplementary source of glaucoma information with improvements in accuracy and readability. Hashtags: #chatGPT #AIChatbotGlaucomaInfo #PatientEducationAI

I'm thrilled to announce the publication of our latest research: "Can Ordinary AI-Powered Tools Replace a Clinician-Led Fracture Clinic Appointment?" Now live on PubMed 💡 What Did We Study? In this study, we evaluated the performance of two AI-powered tools – ChatGPT and Google Gemini – in managing simple fractures. We compared their recommendations with actual clinician-led fracture clinic plans. With AI becoming an integral part of healthcare, we asked: Can AI match the precision and nuance of human expertise in orthopaedic care? 📊 What Did We Find? 🔹 ChatGPT aligned with clinician recommendations in 34% of cases, outperforming Google Gemini (19%), but both tools showed significant limitations. 🔹 AI struggled with personalized treatment plans, often overgeneralizing or oversimplifying cases. 🔹 The findings confirmed that AI tools currently lack the clinical precision required to replace human expertise. 🤔 Why Does This Matter? AI promises to revolutionize healthcare by enhancing efficiency and decision-making, but as our study highlights, the journey is far from over. For now, AI in orthopaedic care should complement, not replace, clinicians. These findings underline the importance of integrating AI outputs with human oversight for safe and effective care. ⚡ A Thought to Ponder: What’s the future of AI in healthcare? Could advances in AI overcome its current limitations, or will human expertise remain irreplaceable in complex clinical decision-making? 📌 Special Thanks This work wouldn’t have been possible without the amazing collaboration of my co-authors and support form mentor Tarek Boutefnouchet 📖 Read the Full Paper Here: https://lnkd.in/ebE5jMJu Let’s continue to explore and shape the future of AI in healthcare, together! 🚀 #AIinHealthcare #Orthopaedics #FractureManagement #ArtificialIntelligence #MedicalResearch

👉🏼 ChatENT: Augmented Large Language Model for Expert Knowledge Retrieval in Otolaryngology-Head and Neck Surgery 🤓 Cai Long 👇🏻 https://lnkd.in/e7_3F-hi 🔍 Focus on data insights: - ChatENT outperformed ChatGPT4.0 in both the Canadian Royal College OHNS sample examination questions challenge and the US board practice questions challenge. - A significant error reduction of 58.4% and 26.0% was observed, respectively. - ChatENT demonstrated enhanced performance in analyzing and interpreting OHNS information, generating fewer hallucinations and showing greater consistency. 💡 Main outcomes and implications: - ChatENT is the first specialty-specific knowledge retrieval artificial intelligence in the medical field utilizing the latest LLM. - Promising applications in medical education, patient education, and clinical decision support are highlighted. - Overcoming limitations of existing LLMs, ChatENT signals a future of more precise, safe, and user-friendly AI applications in OHNS and other medical fields. 📚 Field significance: - Artificial Intelligence - Medical Education - Clinical Decision Support 🗄️: [#Otolaryngology #ArtificialIntelligence #MedicalEducation #ClinicalDecisionSupport]

👉🏼 Caution Regarding ChatGPT's Appropriateness and Reliability Regarding Surgery for Wrist Arthritis 🤓 Keegan Hones 👇🏻 https://lnkd.in/ga5-NGXa 🔍 Focus on data insights: - 📊 75% of responses from ChatGPT were rated as "appropriate," indicating a high level of accuracy in the information provided. - 🔄 The intraclass correlation coefficient (ICC) was 0.97, demonstrating excellent reliability across multiple evaluations. - 📚 The DISCERN score of 60 suggests that the quality of information is good, but there is room for improvement. - 📝 Readability assessments showed a Flesch-Kincaid Grade Level of 14.6, indicating that the content is suitable for a college-level audience. 💡 Main outcomes and implications: - ⚖️ The variability in reliability across different procedures highlights the need for careful evaluation of AI-generated medical information. - 🔍 While some answers were factually correct, many responses lacked specificity, which may limit their practical application in clinical settings. - 🚧 Users must approach AI-generated content with caution, understanding its limitations and potential for generic responses. 📚 Field significance: - 🌐 The findings underscore the importance of integrating AI tools like ChatGPT into medical practice while maintaining critical oversight. - 🏥 This study contributes to the ongoing discourse about the role of AI in healthcare, particularly in patient education and decision-making. - 🔗 It emphasizes the necessity for further research to enhance the accuracy and specificity of AI-generated medical information. 🗄️: [#ChatGPT #AIinHealthcare #WristArthritis #MedicalAccuracy #PatientEducation #Reliability #DataInsights]

Today the most important article in chatgpt and "ChatGPT: is it good for our glaucoma patients?" - ChatGPT's responses required reading comprehension of a higher grade level compared to traditional sources, indicating potential challenges for patient understanding. - The use of specific ophthalmic terms was less frequent in ChatGPT responses compared to established medical resources like the American Academy of Ophthalmology (AAO) website. - The study suggests that while ChatGPT can be effective for providing general information on glaucoma, its repetitive answers and elevated readability scores may pose difficulties for patients. - Recommendations are made for ophthalmologists to consider optimizing content for patient comprehension and accuracy when using AI tools like ChatGPT. #AI #Glaucoma #PatientEducation #Ophthalmology

Ep5: AI in Healthcare–ChatGPT vs Doctors, Remote Patient Monitoring, AI Detecting Disease, AI Surgery Learn how AI is already being used to deliver patients outcomes in healthcare: 😊 Why this is important to Ben–Great Ormond Street Hospital 💡 Remote patient monitoring–David Lubarsky, Vice Chancellor of Human Health Sciences and CEO for UC Davis Health 💡 Sepsis detection–Dr. Tom Mihaljevic , Cleveland Clinic CEO 💡 Implementation of Sepsis detection in hospital environment–Christopher Longhurst MD, Chief Medical Officer and Chief Digital Officer at UC San Diego Health 💡 AI Computer Vision detecting patient falls 💡 E-Con systems patient fall monitoring demo 💡 AI Vision: Imaging outcomes of retina, cariogram and chest X-ray–Physician-scientist Eric Topol, TED Talk 💡 Can AI help with poor patient/doctor communication? 💡 The move from paper to digtal health records and some problems–Robert Wachter of UCSF 💡 ChatGPT vs Doctors–who do patients prefer talking to? John Ayers PhD 💡 Implementing LLM's in the hospital environment–Christopher Longhurst MD 💡 AI outcomes in surgery–Mark Schutzle MD, Division Chief of Orthopaedic Surgery with United Medical Doctors #AI #b2bsales #AIsales #agenticAI #bendrakes #bendrakesuniversity #aioutcomespodcast