Kishlay Anand MD MS’ Post

𝐆𝐏𝐓-𝟒’𝐬 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐢𝐧 𝐬𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐫𝐚𝐝𝐢𝐨𝐥𝐨𝐠𝐲. 🤯 In recent years, AI has been increasingly integrated into healthcare, bringing about new areas of focus and priority, such as diagnostics, treatment planning, patient engagement. While AI’s contribution in certain fields like image analysis and drug interaction is widely recognized, its potential in natural language tasks with these newer areas presents an intriguing research opportunity. Beyond radiology, GPT-4’s potential extends to translating medical reports into more empathetic and understandable formats for patients and other health professionals. This innovation could revolutionize patient engagement and education, making it easier for them and their carers to actively participate in their healthcare. Read complete blog post➡️https://lnkd.in/dcMnFTJa Follow AI Toolhouse - AI Tools Catalogue for more 🥳 #gpts #gpt4 #gptstore #aitools #ai #ml #coding #machinelearning #generatieveai

Shaping the Future of Healthcare with AI Cognitive Services! Discover the game-changing impact of AI in healthcare in our latest Medium article: "The Power of AI in Healthcare: Who Benefits from Cognitive Services?" and learn how cutting-edge cognitive technologies are revolutionizing patient care, diagnostics, and treatment strategies. Read the article now: https://lnkd.in/d5dh3WRp #AIinHealthcare #CognitiveServices #FutureofHealthcare #HealthTechInnovation #PatientCareAI #AICognitiveservices #Marktine #Marktinetechnologies

💡Have you ever wondered what Assistive AI and Generative AI are in healthcare? In this post, we’ll explain the key differences between the two AI models. Assistive AI refers to an AI-based technology designed to assist healthcare professionals in various tasks related to patient care, diagnosis, treatment, and administrative processes. Generative AI, on the other hand, focuses on generating new content relevant to medical research, patient care, and education. #healthcare #AI #GenerativeAI #AssistiveAI #futureofmedicine #artificialintelligence #machinelearning #AIinhealthcare #GenerativeAI  #AssistiveAI

Transforming healthcare with AI The impact on the workforce and organizations AI in healthcare leverages technologies like machine learning, NLP, and robotics to enhance patient care, diagnostics, and administrative tasks. Its applications range from robot-assisted surgeries to virtual nursing assistants and predictive analytics. AI improves diagnostic accuracy, personalizes treatments, and supports remote patient monitoring. Ethical considerations, such as data privacy and algorithmic bias, are crucial. The future of AI in healthcare includes advancements in personalized medicine, mental health interventions, and collaborative efforts to drive innovation. Read more: https://lnkd.in/dwwE3Fwh #rapidinnovation #AIinHealthcare #HealthTech #MedicalInnovation #AIApplications #FutureOfHealthcare

📌 Breakthrough in Medical AI: MedVersa Model 1. Rapid Advancements: Medical AI is transforming diagnosis accuracy and patient care. 2. Current Limitations: Existing AI systems are often limited to narrow applications. 3. Introducing MedVersa: Developed by Harvard, JIPMER, and Scripps, this versatile AI model aims for flexible learning and task handling. 4. Core Innovation: Uses large language models as coordinators, integrating multimodal inputs through language and vision modules. 5. Overcoming Limitations: Combines visual and language supervision, supporting on-the-fly task specifications via language. 6. Exceptional Performance: Excels in tasks like generating radiology reports, visual question answering, anatomical detection, and image segmentation. 7. MedInterp Dataset: A diverse multimodal dataset created for comprehensive medical image interpretation. 8. Superior Results: Outperforms state-of-the-art models in nine tasks on the MedInterp dataset. 9. Radiology Reporting: Surpasses Microsoft’s MAIRA-1 21 and Google’s Med-PaLM M 13. 10. Visual Localization: Outperforms a mature object detector and excels in longitudinal studies, region of interest description, open visual QA, and chest pathology classification. #MedAI #MedVersa #HealthcareInnovation #AI #MedicalResearch #Harvard #Scripps

💡 Propelling innovation in AI and medical device starts with the medical expertise. Check out this article from the Medcase blog, explaining what you need to know about medical data annotation. ⚕ https://lnkd.in/d_KCyNxA #repost

The catch? "Prompt engineering" is the overlooked wildcard. Ordinary users, and yes, even medical professionals, may be clueless about crafting prompts that optimize accuracy. Should doctors loose on generative AI without a clue?. It’s a call for a reality check. AI in healthcare demands awareness. Dr. Eliot's article pushes to Navigate the AI minefield cautiously, or risk healthcare stumbling into uncharted—and potentially perilous—territory. #AIinHealthcare #MedicalSummarization #GenerativeAI #HealthTechDebate #PromptEngineering #AIControversy #HealthcareInnovation #MedicalAIrisks #TechEthics #AIinMedicine

Top 5 AI Platforms for Clinical Decision Making - Clinical & Healthcare #Top5 #AIPlatforms #Clinicaldecesionmaking #Clinical #healthcare These AI platforms in clinical decision-making utilize advanced technologies such as artificial intelligence, machine learning, and natural language processing to assist healthcare professionals and patients in various aspects of healthcare delivery, including diagnosis, triage, treatment planning, and medical imaging analysis. These platforms leverage artificial intelligence to analyze medical data, interpret symptoms, and provide evidence-based recommendations to support clinical decision-making and improve patient care outcomes.

Sometimes, a visit to the doctor for an X-ray is a necessity. Apart from having to endure the long queue, when you are in pain, the time until your results arrive can seem endless. Let’s take a look at how #AI can be integrated into #medical facilities to automate medical imaging for better #screening and faster results. See our new article about the AI application in #Diagnostics using technologies like #computervision, data augmentation, and #imagegeneration! Contact TechnoLynx for tailor-made AI solutions, designed specifically for your business needs!

Last week Google released a new paper on X-ray AI system through alignment of large language models (#LLMs) and radiology vision encoders. ✅ ELIXR is short for Embeddings for Language/Image-aligned X-Rays ✅ It enables efficient training of multimodal models using routinely collected medical images and their associated text reports, and adds the ability to perform a diverse range of tasks with rich expressive outputs ✅ This approach unlocks the potential for a new generation of medical AI applications, supporting workflows including high performance zero-shot and data-efficient classification, semantic search, visual question answering (VQA), and radiology report quality assurance (QA)🚀 ✅ ELIXR has achieved state-of-the-art performance on zero-shot chest X-ray classification🔥🔥 Would be very keen to see more development on top of #EXILR in two directions: 💭Having this in API which can be ultimately given to the doctors as a real 'AI-enabled' assistant. 💭Extrapolating this work to other medical diagnosis - Heartbeat palpations is something which would be on top of my list. Kudos to Andrew Sellergren, Krish Eswaran and the whole team behind this really interesting work. Read the full paper here: https://lnkd.in/gf7ZBuDb #AI #medicaladvancements #innovation #artificialintelligence #generatieveai