Rashmee Shah

The article from Analytics Insights discusses the growing demand for AI skills in healthcare and the introduction of new courses focused on medical engineering and AI applications in medicine. It highlights the University of Michigan's new master's program in Medical Engineering and Physician-Engineering, which aims to train students in using AI, machine learning, and data science for healthcare solutions. The program covers topics like AI for medical imaging, computational genomics, and digital health technologies. It emphasizes interdisciplinary collaboration between engineers, clinicians, and data scientists to develop innovative AI-driven healthcare applications. The article also mentions the University of Pennsylvania's new graduate certificate program in AI for Healthcare, which teaches students how to apply AI techniques like deep learning and natural language processing to healthcare challenges. In summary, the article underscores the increasing integration of AI in healthcare and the need for specialized education programs to equip the next generation of professionals with the skills to leverage AI for improving patient outcomes, clinical decision-making, and healthcare delivery. https://lnkd.in/eS9f-uH3 #healthcare #healthcareinnovation #healthcareit #healthcareai #ai #MedicalEngineering

👉🏼 ChatGPT's Performance in Clinical Decision-Making: A Comparative Study of NASS Guidelines and AI Responses 🤓 Ankur Kayastha 👇🏻 https://lnkd.in/ebFtSS7G 🔍 Focus on data insights: - 📊 ChatGPT-4.0 demonstrated a 67% accuracy rate compared to 47% for ChatGPT-3.5, indicating improved performance in clinical queries. - 📉 The study revealed that ChatGPT-3.5 provided 100% supplementary information, while ChatGPT-4.0 reduced this to 67%, suggesting a more concise response style. - 🔍 Diagnostic testing accuracy improved significantly from 0% in ChatGPT-3.5 to 100% in ChatGPT-4.0, highlighting advancements in AI capabilities. 💡 Main outcomes and implications: - ⚖️ The findings suggest that while both versions of ChatGPT show reasonable concordance with established NASS guidelines, there is a need for caution in clinical applications due to potential misinformation. - 🧠 The study emphasizes the importance of continuous improvement in AI tools for clinical decision-making, as higher accuracy can lead to better patient outcomes. - 🔄 The results advocate for further research into AI's role in healthcare, particularly in enhancing diagnostic and treatment recommendations. 📚 Field significance: - 🌐 The integration of AI in clinical settings could revolutionize how healthcare professionals access and utilize medical guidelines. - 🏥 Improved AI performance may lead to more efficient decision-making processes, ultimately benefiting patient care and resource management. - 🔬 This study contributes to the growing body of literature on AI's effectiveness in medicine, paving the way for future innovations and applications. 🗄️: [#AI #ChatGPT #ClinicalGuidelines #NASS #Healthcare #DecisionMaking #DiagnosticAccuracy #PatientCare #ArtificialIntelligence]

👉🏼 Evaluating the Accuracy, Comprehensiveness, and Validity of ChatGPT Compared to Evidence-Based Sources Regarding Common Surgical Conditions: Surgeons' Perspectives 🤓 Hazem Nasef 👇🏻 https://lnkd.in/eFKvmkVV 🔍 Focus on data insights: - Surgeons rated evidence-based sources as significantly more comprehensive and valid compared to ChatGPT for material discussing acute cholecystitis and upper gastrointestinal hemorrhage. - No significant difference in accuracy was found between evidence-based sources and ChatGPT across the majority of surveyed surgical conditions. 💡 Main outcomes and implications: - Evidence-based sources were perceived as more reliable in terms of comprehensiveness and validity by surveyed U.S. board-certified practicing surgeons. - ChatGPT may have potential benefits in surgical practice but requires further refinement and validation to enhance its utility and acceptance among surgeons. 📚 Field significance: - The study highlights the importance of relying on evidence-based sources for accurate and comprehensive information in the field of surgical practice. - Further research is needed to explore the integration of AI tools like ChatGPT in surgical decision-making processes. 🗄️: [#surgicalpractice #ChatGPT #evidencebasedsources #datainsights]

👉🏼 Using Large Language Models to Support Content Analysis: A Case Study of ChatGPT for Adverse Event Detection 🤓 Eric C Leas 👇🏻 https://lnkd.in/eXmHPwYC 🔍 Focus on data insights: - ChatGPT closely approximated human results in detecting adverse events (AEs) with a high degree of agreement. - The study highlights the potential of large language models to accurately and efficiently replicate human annotation. - Possible limitations include concerns about generalizability due to ChatGPT's training data. 💡 Main outcomes and implications: - ChatGPT demonstrated a 94.4% agreement with human annotators in detecting any AEs and 99.3% agreement for serious AEs. - The study suggests that large language models like ChatGPT can enhance the efficiency of biomedical research by supporting content analysis tasks. - Further research is encouraged to explore different models, data sources, and content analysis tasks for broader applications. 📚 Field significance: - Large language models offer promising opportunities to improve the accuracy and efficiency of content analysis in various fields. - Integrating AI technologies like ChatGPT can streamline data processing and analysis, potentially revolutionizing research methodologies. 🗄️: [#largeLanguageModels #contentAnalysis #biomedicalResearch #ChatGPT #dataInsights]

👉🏼 Multi-Role ChatGPT Framework for Transforming Medical Data Analysis 🤓 Haoran Chen 👇🏻 https://lnkd.in/eu9aMJGr 🔍 Focus on data insights: - The Multi-Role ChatGPT Framework (MRCF) enhances ChatGPT's performance in medical data analysis. - MRCF optimizes prompt words, integrates real-world data, and implements quality control protocols. 💡 Main outcomes and implications: - MRCF outperforms traditional manual analysis in interpreting medical data with fewer errors and higher accuracy. - MRCF is over 600 times more time-efficient than conventional manual annotation methods and costs only one-tenth as much. 📚 Field significance: - This research offers valuable insights for data analysis models in various professional domains. 🗄️: #MedicalDataAnalysis #ChatGPTFramework #DataInsights

👉🏼 Appropriateness of ChatGPT in Answering Heart Failure Related Questions 🤓 Ryan C King 👇🏻 https://lnkd.in/e2e82tuB 🔍 Focus on data insights: - GPT-4 provided 100% correct responses to heart failure-related questions. - GPT-4 displayed a higher proportion of comprehensive knowledge compared to GPT-3.5. - Both models showed high reproducibility in their responses. 💡 Main outcomes and implications: - ChatGPT, specifically GPT-4, can accurately and reliably answer heart failure-related questions. - ChatGPT may be a valuable resource for providing health-related information and education to patients with heart failure. - Further validation and testing are needed to ensure patient safety and equity across all demographics. 📚 Field significance: - Potential use of ChatGPT as a supplemental resource for patients with heart failure. - Importance of rigorous testing and validation for ChatGPT in healthcare settings. 🗄️: #datainsights #healthcare #heartfailure #ChatGPT

👉🏼 Artificial Intelligence Language Models Are Useful Tools for Patients Undergoing Total Ankle Replacement 🤓 Alan P Samsonov 👇🏻 https://lnkd.in/gXcU4aEX 🔍 Focus on data insights: - AI large language models like Chat Generative Pre-trained Transformer (ChatGPT) are effective in providing information to patients undergoing total ankle replacement. - ChatGPT responses were graded as "A," "B," or "C," indicating the quality of information provided. - The study highlights the potential of AI language models in enhancing patient understanding of orthopaedic procedures. 💡 Main outcomes and implications: - ChatGPT provided good-quality responses to common questions about total ankle replacement. - The responses were understandable and aligned with current literature on TAR. - AI language models can serve as valuable resources for patients seeking information on surgical procedures. 📚 Field significance: - AI language models offer a new avenue for patient education and information dissemination in orthopaedic surgery. - Enhancing patient understanding through AI tools can lead to improved patient outcomes and satisfaction. - Further research and development in this area could revolutionize patient care in orthopaedics. 🗄️: [#ArtificialIntelligence #LanguageModels #TotalAnkleReplacement #Orthopaedics]

Jan Beger really love the educational potential of this approach. I think that it allows student learners, but even seasoned clinicians to utilize the data That’s right there in front of them. One of the applications I think about is in the clinical setting, we have educational morbidity conferences, and we often use our age old ways of thinking through problems. wouldn’t be exciting to look at the data that we had from a stimulated or synthetic database that had similar features and explore alternate outcomes? the potential to explore other outcomes as generated by this platform gives us even more food for thought. kudos on this post. I look forward to reading the manuscript

6 Ways to Increase Trust in Generative AI in Healthcare Despite high optimism, generative AI (gen AI) adoption in healthcare is stagnant due to trust issues. Deloitte's 2024 survey of 2,000 US adults found that while consumers see benefits like reduced wait times and lower costs, overall adoption has decreased to 37% in 2024 from 40% in 2023. Distrust, especially among millennials and baby boomers, is rising. However, 74% trust doctors and are comfortable with gen AI when overseen by clinicians. Key Strategies: Transparency and Education: Providers should clearly explain gen AI's use, benefits, and limitations, with educational programs to alleviate fears. Data Privacy and Security: Ensuring compliance with regulations like HIPAA and giving patients control over their data builds trust. Human Oversight: Maintaining a significant role for clinicians in the AI process reassures patients. Building Relationships: Strong patient-provider relationships and clear communication about AI's role enhance trust. Addressing Ethical Concerns: Ensuring AI is free from biases and promoting equity is crucial. Continuous Improvement and Feedback: Actively seeking patient feedback and regularly auditing AI systems helps maintain trust. Building trust is essential for integrating gen AI in healthcare, focusing on transparency, education, and collaboration. #aiinhealthcare #genai #trust With the Specialist is a platform that combines artificial intelligence with a board certified neurologist to enhance neurological care in the primary care setting, bringing the neurology consult to the primary care provider. This collaboration with a board certified neurologist builds that trust that is essential. #withthespecialist #neurology #innovation https://lnkd.in/gjRXD-Nd https://lnkd.in/gExrwg2P