Ben Doremus

👉🏼 Enhancing Diabetes Management for Older Patients: The Potential Role of ChatGPT 🤓 Ken Tanaka 👇🏻 https://lnkd.in/ef-cpgSY 🔍 Focus on data insights: - AI technology enhances diabetes education for older individuals - Importance of accuracy in AI integration into healthcare 💡 Main outcomes and implications: - Improved diabetes management for older patients - Need for establishing a framework for AI in healthcare 📚 Field significance: - Direct communication between patients and healthcare providers remains crucial - Technological advancements in diabetes management 🗄️: [#diabetesmanagement #AIintegration #healthcareframework]

👉🏼 ChatGPT Responses to Frequently Asked Questions on Ménière's Disease: A Comparison to Clinical Practice Guideline Answers 🤓 Rebecca A Ho 👇🏻 https://lnkd.in/e7Nvpwzw 🔍 Focus on data insights: - ChatGPT-4.0 had significantly better resource reporting compared to ChatGPT-3.5. - Both models showed room for improvement in comprehensiveness, readability, and accuracy. 💡 Main outcomes and implications: - ChatGPT-4.0 demonstrated higher quality resources in responses. - Readability scores for both models fell below the recommended level. - Improvement needed in providing more comprehensive and less misleading information to patients. 📚 Field significance: - Evaluating AI models like ChatGPT against clinical guidelines can help identify areas for enhancement in patient education. - Enhancing AI models' readability and accuracy is crucial for effective patient communication in healthcare settings. 🗄️: [#Ménière'sDisease #AIModelEvaluation #PatientEducation #HealthcareCommunication]

👉🏼 Comparing Provider and ChatGPT Responses to Breast Reconstruction Patient Questions in the Electronic Health Record 🤓 Daniel Soroudi 👇🏻 https://lnkd.in/eBGKedQw 🔍 Focus on data insights: - 📊 Combined provider responses had significantly better readability scores compared to all chatbot responses, indicating a potential gap in patient communication effectiveness when using AI. - 🤖 ChatGPT demonstrated higher empathy scores than human providers, suggesting AI can enhance emotional engagement with patients. - 🔍 There was no significant difference in accuracy between providers and chatbot responses, showcasing that AI can match professional accuracy under certain conditions. 💡 Main outcomes and implications: - ⚖️ The findings indicate that while ChatGPT is effective in empathy and accuracy, improvements are needed in readability for it to be a viable communication tool in clinical settings. - 🩺 This study suggests that integrating AI tools could alleviate some communication burdens on healthcare providers, potentially enhancing the overall patient experience. - 📈 The results advocate for further adjustments in AI tools to ensure they meet the necessary standards for patient education and support in medical decision-making. 📚 Field significance: - 🌐 The exploration of AI in patient communication opens avenues for improving healthcare delivery in diverse settings, particularly in specialty fields like plastic surgery. - 🧠 This research contributes to the ongoing discourse about the role of AI in healthcare, emphasizing both its capabilities and limitations. - 🛠️ The study serves as a foundation for future research on optimizing AI tools to better assist healthcare providers while maintaining high standards of patient interaction. 🗄️: [#patientcommunication #AIinhealthcare #breastreconstruction #ChatGPT #medicaleducation #empathy #readability #healthcareproviders #EHR]

👉🏼 ChatGPT compared to national guidelines for management of ovarian cancer: Did ChatGPT get it right? - A Memorial Sloan Kettering Cancer Center Team Ovary study 🤓 Lindsey Finch 👇🏻 https://lnkd.in/esWx_ZsJ 🔍 Focus on data insights: - 📊 64% of unprompted GPT responses were accurate and complete, indicating strong performance in comparison to NCCN guidelines. - 🔍 GPT-4 outperformed NCCN in areas such as risk factors, surgical management, and surveillance, showcasing its potential utility in these domains. - ⚠️ Inaccuracies were noted in medical management questions, highlighting the need for caution in relying solely on AI for clinical decision-making. 💡 Main outcomes and implications: - 🏥 The study suggests that while GPT-4 can provide valuable insights, it should not replace expert clinical judgment, especially in complex cases. - 📈 The findings indicate a growing role for AI in oncology, but emphasize the importance of supervised use to mitigate risks associated with inaccuracies. - 🔄 Continuous evaluation and improvement of AI models are necessary to enhance their reliability in clinical settings. 📚 Field significance: - 🌐 This research contributes to the ongoing discourse on integrating AI into healthcare, particularly in oncology, where timely and accurate information is critical. - 🧠 It underscores the potential of AI tools to assist healthcare professionals, while also calling for rigorous validation against established guidelines. - 🔗 The study paves the way for future investigations into the effectiveness of AI in various medical specialties, promoting a balanced approach to technology adoption. 🗄️: [#ovariancancer #AIinHealthcare #ChatGPT #NCCNGuidelines #oncology #medicalmanagement #surgicalmanagement #riskfactors #healthcareinnovation]

👉🏼 The performance of large language model powered chatbots compared to oncology physicians on colorectal cancer queries 🤓 Shan Zhou 👇🏻 https://lnkd.in/gQ9hfQq3 🔍 Focus on data insights: - Large language model (LLM)-powered chatbots outperformed oncology physicians in accuracy. - Claude 2.1 demonstrated the highest accuracy among the chatbots. - ChatGPT-3.5 had the lowest accuracy among the chatbots. 💡 Main outcomes and implications: - LLM-powered chatbots can provide more accurate medical information than oncology physicians. - Chatbots like Claude 2.1 show potential for improving healthcare information dissemination. - Integration of LLM-powered chatbots in healthcare settings could enhance access to accurate medical information. 📚 Field significance: - Advancements in artificial intelligence, particularly in chatbot technology, are reshaping healthcare information delivery. - Data-driven insights from this study highlight the potential of LLM-powered chatbots in improving medical query responses. - Implications for future research in leveraging AI technologies for enhancing healthcare communication. 🗄️: [#large #language #model #chatbots #oncology #physicians #colorectal #cancer #accuracy #healthcare #AI #technology]

👉🏼 The Performance of a Customized Generative Pre-trained Transformer on the American Society for Surgery of the Hand Self-Assessment Examination 🤓 Jason C Flynn 👇🏻 https://lnkd.in/gCEPBuUZ 🔍 Focus on data insights: - 📊 The customized generative transformer outperformed the standard GPT-4 in text-based question accuracy

👉🏼 Leveraging AI for Enhanced Clinical Simulations in Nursing Education 🤓 Jason A Reid 👇🏻 https://lnkd.in/eft9DS9M 🔍 Focus on data insights: - 📊 ChatGPT significantly reduces the time required for creating clinical simulation scenarios, allowing educators to focus on teaching. - 🧠 The AI generates complex scenarios that enhance critical thinking among nursing students, promoting deeper learning. - ⏱️ The speed of scenario generation enables more frequent and varied simulations, improving overall educational outcomes. 💡 Main outcomes and implications: - 🌟 The integration of AI tools like ChatGPT can transform nursing education by making simulation development more efficient and effective. - 🔄 This shift allows for a more dynamic curriculum that can adapt to the evolving needs of healthcare education. - 📈 Enhanced simulations lead to better-prepared nursing graduates, ultimately benefiting patient care and safety. 📚 Field significance: - 🚀 The use of AI in education represents a significant advancement in instructional methodologies, particularly in competency-based nursing programs. - 🔍 Ongoing research is needed to assess the long-term impacts of AI-generated simulations on student performance and learning retention. - 💬 Discussions around the ethical implications of AI in education are crucial as the field continues to evolve. 🗄️: [#AI #NursingEducation #ClinicalSimulations #ChatGPT #CompetencyBasedEducation #CriticalThinking #EducationalTechnology #InnovativeInstruction]

Look surprised: "healthcare professionals are using LLMs and chatbots to edit writing, make hiring decisions, do administrative tasks, and handle patient data. " https://lnkd.in/d2UMjZqB #research #medicalresearch #medicine #llm #chatbots

👉🏼 Developing large language models to detect adverse drug events in posts on X 🤓 Yu Deng 👇🏻 https://lnkd.in/eXURsJZs 🔍 Focus on data insights: - 📊 The study demonstrates the effectiveness of large language models

👉🏼 Assessment of ChatGPT's Compliance with ESC-Acute Coronary Syndrome Management Guidelines at 30-Day Intervals 🤓 Muhammet Geneş 👇🏻 https://lnkd.in/gqcwwEuN 🔍 Focus on data insights: - 📊 ChatGPT showed initial accuracy of 84% in binary questions, improving slightly to 86% after 30 days. - 🎯 For multiple-choice questions, accuracy improved from 80% to 84%, indicating stable performance over time. - 📈 Cohen's Kappa values

👉🏼 Accuracy, readability, and understandability of large language models for prostate cancer information to the public 🤓 Jacob S Hershenhouse 👇🏻 https://lnkd.in/ek8wbVfg 🔍 Focus on data insights: - GPT-generated output was deemed correct by 71.7% to 94.3% of raters across 9 scenarios. - GPT-generated simplified layperson summaries were rated as accurate in 8 of 9 scenarios. - Mean readability of layperson summaries was significantly higher than original GPT outputs. 💡 Main outcomes and implications: - GPT shows promise for correct patient education for prostate cancer-related content. - Enhancing accuracy, completeness, clarity, and readability of GPT responses can improve its utility in medical chatbots. 📚 Field significance: - Improving the quality of information provided by large language models can enhance patient education and decision-making in healthcare. - Optimizing language model outputs for patient consumption can bridge the gap between complex medical information and public understanding. 🗄️: [#prostatecancer #GPT #patienteducation #healthcare #medicalchatbots]