Health Imaging’s Post

Chatbots, computer programs simulating human conversation, are increasingly used in healthcare. They can help patients, doctors, and researchers in various ways, like providing information, aiding decision-making, and analyzing data. Our recent publication in 'Apollo Medicine' looked at how chatbots are used in medicine now and what the future holds. It found that while chatbots have great potential to improve patient care, research, and daily medical tasks, there are challenges like privacy concerns and the need for more research to ensure their accuracy and safety. Overall, chatbots could make healthcare more accessible, efficient, and better, but it's important to address potential issues before widespread use. #Chatbots, #Helathcare, # Research, #Orthopedics Vijay Kumar Jain, Madhan Jeyaraman, Dr Abhishek Vaish

👉🏼 ChatGPT and the German board examination for ophthalmology: an evaluation 🤓 Rémi Yaïci 👇🏻 https://lnkd.in/esUFm49y 🔍 Focus on data insights: - ChatGPT 4.0 passed the board examination in 12 out of 15 topics. - Overall performance showed 53.3% completely correct answers. - Results varied across topics, with uveitis and lens/cataract scoring 100% while optics and refraction scored 20%. 💡 Main outcomes and implications: - ChatGPT's ability to pass a specialist examination in ophthalmology is noteworthy. - Performance variability across topics highlights limitations for clinical practice. - Thematic fit and internal coherence of answers were generally high. 📚 Field significance: - AI applications like ChatGPT show promise in medical education and assessment. - Further refinement needed to ensure consistent and accurate performance in clinical settings. 🗄️: [#ophthalmology #AI #medicalassessment #ChatGPT]

The ability to integrate artificial intelligence into medicine has been a promise but so far, except for radiology, has been pretty elusive. Google is looking to change that. This is a fascinating new article about how AI might practically be used in medicine. The lawyers Waranch & Brown, LLC are keeping a close eye on these developments because they likely will impact medical malpractice in the future. You need to know the role of AI. #ai #waranchbrown #knowtherole

🚀 𝗔𝗱𝗮𝗽𝘁𝗲𝗱 𝗹𝗮𝗿𝗴𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠𝘀) 𝗱𝗲𝗺𝗼𝗻𝘀𝘁𝗿𝗮𝘁𝗲 𝘁𝗵𝗲𝗶𝗿 𝗽𝗼𝘁𝗲𝗻𝘁𝗶𝗮𝗹 𝘁𝗼 𝗼𝘂𝘁𝗽𝗲𝗿𝗳𝗼𝗿𝗺 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗲𝘅𝗽𝗲𝗿𝘁𝘀 𝗶𝗻 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝘁𝗲𝘅𝘁 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻. 🚀 A recent study published in Nature Medicine showcases how #LLM, when applied to diverse clinical tasks like radiology reports and patient dialogue, produce 𝘀𝘂𝗺𝗺𝗮𝗿𝗶𝗲𝘀 𝘁𝗵𝗮𝘁 𝗮𝗿𝗲 𝗲𝗶𝘁𝗵𝗲𝗿 𝗲𝗾𝘂𝗶𝘃𝗮𝗹𝗲𝗻𝘁 𝗼𝗿 𝘀𝘂𝗽𝗲𝗿𝗶𝗼𝗿 𝘁𝗼 𝘁𝗵𝗼𝘀𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝗱 𝗯𝘆 𝗺𝗲𝗱𝗶𝗰𝗮𝗹 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝘀. This groundbreaking research not only highlights the capabilities of LLMs in natural language processing but also suggests a promising solution to alleviate the documentation burden faced by clinicians. By integrating LLMs into clinical workflows, healthcare providers can streamline the summarization of vast textual data from electronic health records, allowing them to allocate more time to direct patient care. As we witness the transformative impact of AI in healthcare, it prompts us to explore further possibilities for enhancing clinical practice and improving patient outcomes. 🤔 𝗛𝗼𝘄 𝗰𝗮𝗻 𝘄𝗲 𝗵𝗮𝗿𝗻𝗲𝘀𝘀 𝘁𝗵𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝗟𝗟𝗠𝘀 𝘁𝗼 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗮𝗻𝗱 𝗲𝗹𝗲𝘃𝗮𝘁𝗲 𝘁𝗵𝗲 𝘀𝘁𝗮𝗻𝗱𝗮𝗿𝗱 𝗼𝗳 𝗽𝗮𝘁𝗶𝗲𝗻𝘁 𝗰𝗮𝗿𝗲? #llm #artificialintelligence

The Dangers of Self-Diagnosis & Self Testing: Why Medical Expertise Matters Question "have you been tested for any age related illnesses pre Parkinson's or anything like that" - Mika Brzezinski Answer "I've been testing myself, and testing everywhere I go" - President Biden on MSNBC’s Morning Joe In a presentation I give on AI and Medical Treatment/Diagnosis and dangers of AI Hallucination, I discuss AI Medical Diagnosis/Treatment, Self-Diagnosis/Treatment using AI and the dangers of this without proper medical supervision. I make the following points. “A lawyer or person who represents himself has a fool for a client” A patient who self-diagnose/treats themselves without the guidance from a medical professional has a fool for a patient. - because the patient can have an "Unfounded or mistaken impression or notion" - a Hallucinations, a confabulation, a delusion Going from Medical Googling to Medical AI Self Diagnosis/Treatment How Should Clinicians Respond? Hallucinations: AI Telling You What You Want to Hear, Making Up Facts Bard: Top medical self-treatment errors to avoid: #9 Performing self-surgery - Attempting to perform surgical procedures on oneself can cause serious harm. Leave all surgery to trained professionals. Leave all diagnosis to medical professional who are licensed to practice medicine    Humans are constantly hallucinating. We make up stories about ourselves and the world around us. We believe things that are not true. We lie to ourselves and to others - knowingly or unknowingly Does Generative AI hallucinate because it is trained on the human experience that constantly hallucinates - provides information that is not reliable or only tells you what you want to hear or lies to gain something?  Hallucination - Merriam-Webster  1) [DSM-5] a sensory perception (such as a visual image or a sound) that occurs in the absence of an actual external stimulus and usually arises from neurological disturbance 2) Unfounded or mistaken impression or notion, 3) Computing: Plausible but false or misleading response generated by an AI algorithm AI Hallucination (also called confabulation or delusion): a response generated by an AI which contains false or misleading information presented as fact – Bing / Hallucination - Wikipedia Studying hallucinations helps optimize AI output by guiding models to maximize utility and reward functions, reducing misleading information. – Bing #cognitivetesting #AIinHealthcare #MedicalDiagnosis #SelfDiagnosis #AIHallucination #AIandMedicine #MedicalEthics #ResponsibleAI #HealthcareInnovation #AIPolicy

The testing of AI in medicine is a mess. Here’s how it should be done

https://lnkd.in/gHzeAC5E Exploring the Challenges of AI in Medicine 🤖💉 The article "How Do You Test AI in Medicine?" published in Nature delves into the complexities of integrating AI tools into healthcare settings. While hundreds of AI-powered medical devices have been approved, the article highlights the need for rigorous clinical trials and validation to ensure their effectiveness and safety. The discussion brings to light the critical role of human interaction in the successful deployment of AI and the pressing need for standardized testing protocols across institutions. Read more about the challenges and potential solutions in the full article. #AI #HealthcareInnovation #MedicalDevices #ClinicalTrials #Technology

The testing of AI in medicine is a mess. Here’s how it should be done Hundreds of medical algorithms have been approved on basis of limited clinical data. Scientists are debating who should test these tools and how best to do it. https://lnkd.in/dqTqP7A3?

Can you ask AI how to get well? Better get a second opinion…

Nature report: The testing of AI in medicine is a mess. Here’s how it should be done. Hundreds of medical algorithms have been approved on basis of limited clinical data. Scientists are debating who should test these tools and how best to do it. https://lnkd.in/gY-DYzDi Crucial step needs to be fixed in the democratization of GenAI in healthcare. #GenAI #aiTesting #clinicalAI