Keke Qi

🏥AI doctors can treat 10,000 patients in a few days, a task that would take human doctors at least two years. 🩺Research team leader of the Agent Hospital, Liu Yang, said this innovative method enables real doctors to treat virtual patients while also providing medical students with better training. 🔬By simulating various AI patients, students can confidently propose treatment plans without risking harm to real patients, Liu stressed. 🔑"AI hospital town can simulate and predict various medical scenarios, such as the spread, development and control of infectious diseases in a region https://lnkd.in/gH4rcxcF

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✍ Crafting an Effective AI Council Charter in Healthcare & Life Sciences Continuing our ongoing discussions on AI Council for GenAI acceleration (post 1 - https://lnkd.in/eW2QhTKR; post 2 - https://lnkd.in/egbJmTps), let’s dive deeper into what might be literally the first task for AI Council i.e. establishing and maintaining a well-defined AI Council Charter. A well-crafted charter not only mitigates risks but also drives responsible AI innovation. The healthcare and life sciences sector faces unique challenges, including bias in AI algorithms, data privacy concerns, and the complexities of regulatory compliance. Addressing these challenges, as part of their charter, is critical for the success of the AI Council. Drafting a charter as the AI Council's first deliverable sets the tone for expectations and its effectiveness in leading GenAI adoption. This process may benefit from engaging a partner or consultant for a smooth experience. Below, I am sharing my mental model on charter development, giving insight into what it takes to deliver. As a new AI Council of diverse internal leaders, expect to go through norming, storming, and forming stages while drafting a charter. For a common understanding, I recommend members review key documents from government and NGO entities, such as FDA's AI & Medical Products white paper, White House's AI Bill of Rights, WHO's AI health regulations, and EU's AI Act. Give members ample time to familiarize themselves with these materials. Next, invite them for collaborative charter-defining workshops, ideally offsite to avoid distractions. During this 2-4 day event, use design thinking to gather inputs on purpose, scope, goals, challenges, roles, responsibilities, deliverables, KPIs, structure, and alignment with medical/scientific rigor. This iterative process should allow time for idea generation, sharing, grouping, and prioritizing. Using prioritized ideas, facilitate a session for participants to collaboratively draft the charter, combining key elements identified. Define the team's Purpose, Goals, Roles, Responsibilities, KPIs, Deliverables, and Structure. Allow ample time to ensure alignment and commitment from your cross-functional AI Council. Next, seek council feedback on clear, measurable KPIs (e.g., AI implementations, compliance rates) to gauge effectiveness. Align on audit cadence and PMO support. Consider additional measures: communication strategy, surveys, ethical incident analysis, impact assessments, and benchmark comparisons. These ensure the charter evolves with the AI landscape, remaining a living document. 💬 Have you defined your AI Council's charter? 📢 Subscribe to my newsletter: https://lnkd.in/g3bdneR7 #genai #ai #aws #AIinHealthcare #ResponsibleAI #LifeSciences

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𝐊𝐢𝐦𝐛𝐞𝐫𝐥𝐲 𝐏𝐨𝐰𝐞𝐥𝐥, 𝐭𝐡𝐞 𝐕𝐢𝐜𝐞 𝐏𝐫𝐞𝐬𝐢𝐝𝐞𝐧𝐭 𝐨𝐟 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐚𝐭 𝐍𝐯𝐢𝐝𝐢𝐚, 𝐞𝐦𝐩𝐡𝐚𝐬𝐢𝐳𝐞𝐝 𝐭𝐡𝐞 𝐬𝐢𝐠𝐧𝐢𝐟𝐢𝐜𝐚𝐧𝐭 𝐢𝐦𝐩𝐚𝐜𝐭 𝐀𝐈 𝐢𝐬 𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝 𝐭𝐨 𝐡𝐚𝐯𝐞 𝐨𝐧 𝐡𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞, 𝐦𝐨𝐫𝐞 𝐭𝐡𝐚𝐧 𝐚𝐧𝐲 𝐨𝐭𝐡𝐞𝐫 𝐬𝐞𝐜𝐭𝐨𝐫. Here are the key points from her talk at Nvidia’s AI Summit: 1️⃣ 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐢𝐧 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞: Generative AI is revolutionizing the healthcare industry and is set to transform pharmaceutical research, patient diagnostics, and post-operative care. 2️⃣ 𝐀𝐈 𝐢𝐧 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲: AI is expected to drastically change drug discovery and development, a process that traditionally takes up to 15 years and can cost around $2 billion. Generative AI can explore the vast chemical space, which contains an estimated 10 to 60th power potential chemical compounds. AI’s ability to model interactions between new chemical compounds and the human body can help reduce the 90% failure rate of drugs in clinical trials. 3️⃣ 𝐍𝐯𝐢𝐝𝐢𝐚’𝐬 𝐅𝐨𝐜𝐮𝐬 𝐨𝐧 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞: Nvidia, now the world’s third-biggest company by stock value, has made healthcare a key area of focus. They are developing platforms, software, and medical devices aimed at improving digital imaging, diagnostic scans, and robot-assisted surgery. In March, Nvidia announced partnerships with #Johnson & Johnson and #GE Healthcare to integrate AI into surgical procedures and medical imaging, respectively. 4️⃣ 𝐀𝐈 𝐢𝐧 𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐈𝐦𝐚𝐠𝐢𝐧𝐠 𝐚𝐧𝐝 𝐒𝐮𝐫𝐠𝐞𝐫𝐲: Technologies used in self-driving cars to process sensor data and make real-time decisions are being adapted for healthcare applications, such as ultrasound imaging and robotic surgery. #AIinHealthcare #GenerativeAI #DrugDiscovery #NvidiaHealthcare #MedicalImaging #RoboticSurgery #HealthcareRevolution #DigitalHealth https://lnkd.in/g45uscZX

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This is a major milestone in medical AI ! And I hope to see more of this in radiology !👇 A Taiwanese team achieved a major feat by conducting a randomized control trial, the gold standard in medical evaluation, to measure the impact of an AI-based ECG alarm on patient mortality – a rock-solid outcome ! The results speak for themselves: AI usage was associated with a remarkable 16% reduction in mortality 🤩 This is a major milestone for cardiology 🫀 While most AI evaluations in radiology focus on intermediate outcomes like diagnostic performance or report turnaround time, this cardiology study delves deeper, emphasizing the importance of assessing effects at patient-level and on hard outcomes such as mortality for widespread adoption of healthcare AI. It's easier to evaluate such effects for acute diseases, where outcomes manifest quickly, unlike diseases like cancer or neurodegenerative conditions. This study serves as a crucial reminder to prioritize bold, hard outcomes over intermediate ones in radiology research. Special thanks to Eric Topol, MD for highlighting this extraordinary study in his newsletter, and kudos to the dedicated research and clinical teams behind this groundbreaking work ! Find the study link in the comments below. #cardiology #AI #RCT #Radiology Illustration : Cardiologs website

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🤓 𝗟𝗲𝘁'𝘀 𝗴𝗲𝘁 𝗻𝗲𝗿𝗱𝘆! Take a look at this Amazon Web Services (AWS) blog about "Project Heal" – an AI-powered toolkit designed for the early detection and mitigation of medical misinformation. The blog does an excellent job of explaining some the technical components of the system. Here are some highlights: 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝘆𝗶𝗻𝗴 𝗠𝗶𝘀𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 “One of the key functionalities of Project Heal will be the ability to classify and detect emerging misinformation before it has an opportunity to proliferate.” “Ingested information will be evaluated using trained ML models, enabling the tool to classify the likelihood of a statement having misleading content and allowing for categorization based on the statement’s entities and context.” “Misleading statements will then be evaluated by a subsystem to help score the severity of the threat to human health.” “The detection engine will be built using graph neural networks, which will be supported by a large, scalable, fully managed graph database (Amazon Neptune). Amazon Comprehend will be used to support keyword and entity extraction from content.” “A human feedback loop will consistently audit and improve the model using Amazon Augmented AI (Amazon A2I).” “Both detection and scoring will be supported by Amazon SageMaker, a fully managed service to prepare data and build, train, and deploy ML models for any use.” “Additionally, generative AI will support the summarization and grouping of related misinformation content.” 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗖𝗼𝘂𝗻𝘁𝗲𝗿 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 “One of the most innovative features of Project Heal will be the platform’s ability to generate tailored communication responses to misleading information.” “To achieve this, Project Heal will use generative AI foundation models (FMs) through Amazon Bedrock, such as Amazon Titan.” “Supporting evidence, built from trusted sources of information, will be available to users via Retrieval-Augmented Generation (RAG), an approach that reduces some of the shortcomings of large language model (LLM)-based queries.” “Through this technique, Amazon Bedrock is able to generate more personalized messaging by combining trusted information and user preferences.” 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲 This project illustrates the complexity of developing AI-driven solutions and the importance of integrating them thoughtfully to tackle real-world challenges such as medical misinformation. 🙂 With these insights, I hope I’ve satisfied your nerdy needs! https://lnkd.in/e3gzR7XG

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🌟 **Revolutionizing Clinical Development with AI and Digital Twins** 🌟 As SVPs & Heads of Clinical Development, we understand the immense pressure to reduce trial timelines, costs, and uncertainty while ensuring the highest standards of patient care. Traditional clinical development often grapples with: ✔️Prolonged timelines ✔️Escalating costs ✔️Unpredictable patient outcomes. ⁉️ The question that echoes through our halls: How do we bring life-saving treatments to patients faster and more efficiently? 🤔 Enter **AI and Digital Twins** – the game-changers in our industry. 🦾✨ 🔍 **What Are Digital Twins?** Digital twins are sophisticated AI models that replicate patient-level data. Essentially, they are virtual representations of each patient in a clinical trial, allowing us to simulate and predict health outcomes with remarkable accuracy. These digital entities enable us to: 1. **Accelerate Trial Timelines** ⏱️ - By utilizing digital twins, we can simulate numerous clinical scenarios in a fraction of the time, drastically reducing the duration of traditional trials. 2. **Cut Costs** 💰 - Traditional trials are often resource-intensive. Digital twins significantly reduce the number of necessary physical trials, leading to tremendous cost savings. 3. **Increase Certainty in Outcomes** 🔮 - Predictive analytics from digital twins provide early insights into patient responses, enabling more informed decision-making and enhancing trial precision. 👉 **Why Digital Twins Matter** Incorporating digital twins transforms clinical development from a reactive process to a proactive and predictive one. The impact? Faster delivery of life-saving treatments to patients who need them most, reducing the suffering from prolonged waiting times. This is not just an operational improvement; it is a leap towards more humane and patient-centric clinical development. 🌐 **Join the Revolution** Our commitment to integrating digital twins in clinical trials is paving the way for a new era in biotechnology. We are not just optimizing processes; we are enhancing patient lives by ensuring a swifter journey from research to treatment. As leaders in this field, it’s our mission to embrace and advocate for these technological advancements. The future of clinical development is here and now. Let’s work together to harness this potential and transform patient care across the globe. 🌍💉 #ClinicalDevelopment #Biotechnology #AI #DigitalTwins

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eHealth Exchange President, Jay Nakashima will speak tomorrow at the Japanese Society for Medical Informatics. The conference theme is "connecting". Jay lived in Japan when he worked for IBM in his 20's, and it is an honor for him to return to Tokyo and share how eHealth Exchange achieved the nationwide trust necessary to electronically exchange patients’ detailed medical records at scale, along with lessons learned and recommendations. #datasharing #interoperability #healthcareIT https://buff.ly/3RkWL6K

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In today's healthcare landscape, the integration of advanced technology such as AI and Machine Learning is reshaping how healthcare providers and medical device manufacturers are delivering value across the health continuum. Learn about the latest healthcare software advancements, gain insights from industry experts, and be inspired by our client’s success stories. Follow FPT Americas to discover how technology is shaping the future of healthcare.

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Suki Launches SDK to Power Voice AI Experiences with Bond Vet - HIT Consultant #Suki Launches SDK for Voice AI Experiences with Bond Vet #Introduction Suki, a healthcare AI company, has launched an SDK to enhance voice AI experiences with Bond Vet, a veterinary care provider. #Benefits of Voice AI in Healthcare Voice AI technology offers numerous benefits in healthcare, including improved efficiency, accuracy, and patient satisfaction. #Suki's SDK Features The SDK from Suki provides advanced voice AI capabilities for seamless integration with Bond Vet's systems. #Enhancing Patient Care By leveraging Suki's SDK, Bond Vet can enhance patient care through voice-enabled interactions and streamlined workflows. #Future of Voice AI in Healthcare The collaboration between Suki and Bond Vet signifies a promising future for voice AI technology in the ai.mediformatica.com #suki #health #platform #voice #technology #healthcare #voiceai #documentation #electronichealthrecord #healthcaretechnology #software #softwaredevelopment #digitalhealth #healthit #healthtech @MediFormatica (https://buff.ly/3X4P88l)

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🏥 🌟 Creating a GenAI-Ready Culture Deloitte’s Generative AI Survey (https://lnkd.in/eUCuhZhK) found that the pace of GenAI adoption is moving rapidly, with nearly half (47%) of all respondents saying they are moving fast with their adoption. For organizations with very high GenAI expertise, the adoption rate is even higher at 73%. Here's how enterprise leaders can foster a culture embracing GenAI: 1. 🎯 Align with Purpose: Connect GenAI adoption to the elevated purpose of serving mankind. Highlight its potential to improve patient outcomes, streamline drug development, and advance scientific discovery. 2. 🤝 Collaborate and Share Knowledge: Establish a GenAI council to enable, prioritize, and share ideas and best practices across functions. Encourage partnerships with research institutions and startups to drive innovation. 3. 📚 Upskill and Reskill: Equip employees with the necessary skills and knowledge to navigate the world of GenAI in healthcare and life sciences. Provide tailored training opportunities to build AI proficiency. 4. 🔬 Experiment and Learn: Create opportunities for employees to experiment with GenAI in a safe environment. Encourage trial and error, and celebrate learnings from both successes and failures. 5. ⚖ Address Ethical Considerations: Develop guidelines and principles to ensure responsible GenAI use, considering ethical, privacy, and security implications specific to healthcare and life sciences. 6. 🔎 Build Trust and Transparency: Demonstrate GenAI's capabilities and limitations, encouraging open communication and feedback to address concerns and continuously improve GenAI solutions. 7. 📜 Establish Governance and Accountability: Clearly define roles and responsibilities related to GenAI initiatives, ensuring alignment with strategic objectives and regulatory requirements. 💬 Share your experiences and insights on adopting GenAI in the comments below! 📢 Subscribe to my newsletter to get access to strategies and practical guidance on accelerating adoption of generative AI within your organization. Get started here: https://lnkd.in/g3bdneR7 #genai #ai #aws #lifesciences #healthcare

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🌟 📈 Organizational Change Management: Empowering Generative AI Adoption in the Business Landscape Healthcare and Life Sciences firms must focus on developing robust change management capabilities to help their organizations adapt and thrive in the face of the disruption and transformation opportunities presented by Generative AI. By educating line-of-business leaders on NLP's (Natural Language Processing) potential and partnering with technology teams, GSIs, ISVs, and top consulting firms, organizations can harness the power of generative AI to optimize business processes and maximize ROI. Key considerations for effective organizational change management in the context of generative AI adoption include: 1. 🎓 Education and Awareness: Equip line-of-business leaders with the knowledge of NLP and its impact on their respective functions, enabling them to identify opportunities and risks associated with AI-driven transformation. The current Generative AI powered by Large Language Models (LLMs) represents just one application of NLP technology. Future enhancements and innovations in this field are expected to expand beyond text, encompassing vision-based capabilities for processing images, live videos, and task based actions as well. 2. 🤝 Partnership and Collaboration: Encourage cross-functional collaboration between business leaders, technology teams, ISVs, and consulting partners to develop a comprehensive playbook and roadmap for AI adoption. By partnering with Independent Software Vendors (ISVs) that specialize in generative AI solutions for the industry, organizations can accelerate adoption and promote faster time-to-market for generative AI-driven innovations. 3. 💰 ROI and Prioritization: Large organizations often accumulate a patchwork of back-office processes over time, resulting in complex, multi-layered systems. Many of these legacy workflows are prime candidates for optimization through the application of generative AI technologies and could save organizations millions of dollars! Effective organizational change management is crucial for businesses looking to capitalize on the immense potential of generative AI. By fostering a culture of collaboration, continuous learning, and strategic alignment, organizations can pave the way for a successful and impactful AI-driven future. 💬 Share your experiences and insights on navigating the organizational change management process in the context of generative AI adoption below! 📢 Subscribe to my newsletter to get access to strategies and practical guidance on accelerating adoption of generative AI within your organization. Get started here: https://lnkd.in/g3bdneR7 #OrganizationalChangeManagement #OCM #NLP #BusinessTransformation #GenerativeAI #HealthcareInnovation #pharmaceutical #biopharma #biotech #aws #AmazonBedrock #ChangeManagement #innovation #genai #lifesciences #healthcare #patientcare #ai #clinicalresearch #clinicaltrial #partnership #aiadoption #coe #ai #customersuccess

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Ever feeling lost when you need to see a doctor? Alipay's Angel, an AI-enabled digital healthcare assistant, is making hospital visits easier, with pilot projects already rolled out in Zhejiang, China. Watch the video to see how Angel can help👇 #AIinAlipay #AIHealthcare #HealthTech

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