AI meets Rheumatology: ChatGPT and patient response optimization Large language models like ChatGPT, trained on vast text data, are revolutionizing healthcare by understanding and generating human-like language.
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AI meets Rheumatology: ChatGPT and patient response optimization Large language models like ChatGPT, trained on vast text data, are revolutionizing healthcare by understanding and generating human-like language.
AI meets Rheumatology: ChatGPT and patient response optimization | RheumNow
rheumnow.com
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Healthcare Operations Strategist | Managed Care Specialist | Process Management | Data Analysis & Reporting
This article from MedCity News discusses how large language models (LLMs) like ChatGPT can enhance the patient experience in healthcare. The piece highlights the potential of using LLMs in tasks such as answering patient queries, providing personalized health information, and improving communication between patients and healthcare providers. Additionally, the article explores the challenges and ethical considerations associated with implementing LLMs in healthcare settings. https://lnkd.in/ea-EA3Na #healthcare #healthcareai #healthcareit #ai #genai #llm #generativeai #ChatGPT
How Large Language Models Will Improve the Patient Experience - MedCity News
https://medcitynews.com
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Many consumers and medical providers are turning to chatbots, powered by large language models to answer medical questions and inform treatment choices. Five major large language models was subjected to parts of the U.S. Medical Licensing Examination Step 3 examination, widely regarded as the most challenging. Here’s how ChatGPT, Claude, Google Gemini, Grok and Llama performed. ChatGPT-4o (OpenAI) — 49/50 questions correct (98%) Claude 3.5 (Anthropic) — 45/50 (90%) Gemini Advanced (Google) — 43/50 (86%) Grok (xAI) — 42/50 (84%) HuggingChat (Llama) — 33/50 (66%) #AI #LLM #healthcare #doctors Scott Gottlieb https://lnkd.in/dqAvmN-9
Op-ed: How well can AI chatbots mimic doctors in a treatment setting? We put 5 to the test
cnbc.com
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Is it time to reevaluate the reliability of LLMs like ChatGPT in medicine? The increasing reliance on LLMs, including ChatGPT, in the medical field is prompting some timely critical examination of their reliability. A recent study by Stanford HAI reveals a troubling gap: even cutting-edge models often fail to substantiate their answers, casting doubt on their suitability for medical decision-making. As the role of AI in medicine continues to evolve, it's imperative that we prioritise the development and use of reliable, evidence-based tools that both support healthcare professionals and deliver optimal outcomes for patients. Metadvice is at the forefront of leveraging AI to manage long-term chronic conditions and therefore tackling the global challenges of healthcare systems. #AIHealthcare #DigitalHealth #PatientCare #Innovation
Reports tell us that doctors are increasingly using #ChatGPT in their day-to-day work, and a growing number of patients are using LLMs (large language models) to self-diagnose. This begs the question: Is ChatGPT gradually replacing the role of the Doctor? Moreover, is it safe? According to a recent study from the Stanford Institute for Human-Centered Artificial Intelligence (HAI), “Very little evidence exists about the ability of LLMs to substantiate claims," adding that most LLMs struggle to produce relevant sources, and ~30% of individual statements made on models like ChatGPT are unsupported. Yet there ARE opportunities for AI to transform the healthcare landscape now. Our AI-driven platform provides evidence-based recommendations, using the latest relevant guidelines, so clinicians can deliver informed, effective treatment. We look forward to seeing developments in this space, to support patients, clinicians, and health systems alike - with safety at the forefront. Read more about the study by Kevin Wu, Eric Wu, Daniel Ho, and James Zou: https://lnkd.in/gfcDDBut #HealthcareAI #LLMs #FutureofHealthcare
Generating Medical Errors: GenAI and Erroneous Medical References
hai.stanford.edu
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👍 Many consumers and medical providers are turning to chatbots, powered by large language models, to answer medical questions and inform treatment choices. Here's how ChatGPT, Claude, Google Gemini, Grok and Llama performed. Transformation wirh Technology 👌
Op-ed: How well can AI chatbots mimic doctors in a treatment setting? We put 5 to the test
cnbc.com
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Reports tell us that doctors are increasingly using #ChatGPT in their day-to-day work, and a growing number of patients are using LLMs (large language models) to self-diagnose. This begs the question: Is ChatGPT gradually replacing the role of the Doctor? Moreover, is it safe? According to a recent study from the Stanford Institute for Human-Centered Artificial Intelligence (HAI), “Very little evidence exists about the ability of LLMs to substantiate claims," adding that most LLMs struggle to produce relevant sources, and ~30% of individual statements made on models like ChatGPT are unsupported. Yet there ARE opportunities for AI to transform the healthcare landscape now. Our AI-driven platform provides evidence-based recommendations, using the latest relevant guidelines, so clinicians can deliver informed, effective treatment. We look forward to seeing developments in this space, to support patients, clinicians, and health systems alike - with safety at the forefront. Read more about the study by Kevin Wu, Eric Wu, Daniel Ho, and James Zou: https://lnkd.in/gfcDDBut #HealthcareAI #LLMs #FutureofHealthcare
Generating Medical Errors: GenAI and Erroneous Medical References
hai.stanford.edu
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I find this article of Stanford Institute for Human-Centered Artificial Intelligence (HAI) particularly compelling as it discusses the increasing presence of LLMs such as ChatGPT in the healthcare sector. It emphasizes the importance of evaluating their reliability, despite their potential to assist in diagnosis. However, lingering concerns about their accuracy remain prevalent. 🔍 Verifying References: A Key Challenge ▶ Recent study highlights LLMs' struggle to cite medical sources accurately. ▶ 30% of statements from advanced models like GPT-4 remain unsupported. Even with retrieval augmented generation (RAG) models, errors persist. 📈 Evaluating Performance: ▶ LLMs perform best with inquiries based on professional medical texts. ▶ Lay inquiries, particularly from platforms like Reddit, pose greater challenges. 🔍 Importance of Source Verification: ▶ Health knowledge democratization hinges on LLMs' ability to provide reliable information. ▶ Currently, LLMs fall short, raising concerns about their distributive effects on health knowledge. 🔬 Looking Ahead: ▶ Research should focus on domain-specific adaptations, like RAG for medical use. ▶ Regular evaluation of source verification is crucial for ensuring credibility. 👩⚕️ Regulatory Considerations: ▶ As LLMs gain prominence, regulators and healthcare providers must scrutinize their integration and reliability. Link to the article: https://lnkd.in/ebMcF64p Thanks to the authors: Kevin Wu Eric Wu Daniel E. Ho James Zou Other leaders working and advising in generative AI: Chaitanya Adabala Viswa Delphine Nain Zurkiya Joachim Bleys Bhavik Shah Eoin Leydon Mahmoud Abu Eid ASLI AKSU Eric Bruckner Lucia Darino Supreet Deshpande Alex Devereson Aliza Dzik Anas El Turabi Lionel Jin Matej Macak Abhi Raj Rajendran Boyd Spencer Hann-Shuin Yew Stephen Chase Amy Matsuo Emily Frolick Bryan McGowan Brian Consolvo Kanika Saraiya Havelia Christopher Montgomery Meg Smiley Wheaton The journey toward harnessing LLMs' potential in healthcare requires rigorous evaluation and continuous improvement.
Generating Medical Errors: GenAI and Erroneous Medical References
hai.stanford.edu
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Generative artificial intelligence continues to make impressive strides in medicine. While the healthcare industry has been grappling with the anecdotal notions of ChatGPT’s superior soft skills, a recent study published in the Journal of the American Medical Association provides hard evidence. The team concluded that 80% of the AI-generated responses as more nuanced, accurate and detailed than those shared by physicians. But most surprising was ChatGPT’s bedside manner. According to a write up in U.S. News, “While less than 5% of doctor responses were judged to be ‘empathetic’ or ‘very empathetic,’ that figure shot up to 45% for answers provided by AI.” Read more >> https://lnkd.in/eDX6eabp #artificialintelligence #innovation #technology
Doctors Vs. ChatGPT: Which Is More Empathetic?
forbes.com
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Empowering organizations to make smarter, and data-driven decisions ⚡ Team Lead & Data & AI Consultant bij Inetum-Realdolmen 🤝📈👥| Python 📈 | AI 🧠 ML 🤖| Azure ☁ | IoT 📶| Power BI 📊| PM | PSM Scrum Master | PRINCE2
*𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐢𝐧 𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞: 𝐚𝐧 𝐨𝐯𝐞𝐫𝐯𝐢𝐞𝐰 𝐨𝐟 𝐢𝐭𝐬 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬, 𝐚𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬, 𝐥𝐢𝐦𝐢𝐭𝐚𝐭𝐢𝐨𝐧𝐬, 𝐟𝐮𝐭𝐮𝐫𝐞 𝐩𝐫𝐨𝐬𝐩𝐞𝐜𝐭𝐬, 𝐚𝐧𝐝 𝐞𝐭𝐡𝐢𝐜𝐚𝐥 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬* ChatGPT has a range of potential applications in the medical field from identifying research topics to assisting in diagnosis. However, these applications come with ethical considerations and limitations. The future prospects of ChatGPT in medicine and healthcare are like a double-edged sword. The ethical aspect will emerge as the main challenge in the coming years of the GenAI era. Here is a peer-reviewed (non technical) article (with 50+ citations) https://lnkd.in/eyDCMVud #ChatGPT #medicalresearch #healthcare #AIinmedicine
ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations
ncbi.nlm.nih.gov
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Are AI-chatbots suitable for hospitals? An interdisciplinary team led by Daniel Rueckert, Professor of Artificial Intelligence in Healthcare and Medicine at TUM and one of our MCML directors, addressed this question in the journal "Nature Medicine". For the first time, doctors and AI experts systematically investigated how successful different variants of the open-source large language model Llama 2 are in making diagnoses. #AIchatbots #health #MedicalAI #LLM
A current study shows that AI-chatbots are not ready for hospital diagnoses. Large language models perform worse than physicians and do not follow guidelines. #AIchatbots #LLMs #MedicalAI #HealthcareAI 📷iStock/S. Lazarenka go.tum.de/576905
Are AI-chatbots suitable for hospitals?
tum.de
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