Alex G. Lee, Ph.D. Esq. CLP

Pearls of Wisdom shared by Jensen Huang 1. 'Startups don't invest in Startups, startups don't partner with startups' 😎 2. 'Before a market exists, you still need early indicators of future success - E-I-O-F-S..I was using it all the time to give the company hope, hey we solve this problem, that problem, the markets didn't exist but they were important problems.. we want to be sustainable and the markets have to exist at some point.. that's how you solve the problem of investing into something that is very far away and having the conviction to stay on the road is to find as early as possible the indicators that you're doing the right things' ✊ 3. 'you want the company to be lazy about doing things that other people always do, can do. If somebody else can do it, let them do it. We should go select things that if we didn't do it, the world would fall apart. If I don't do this, it won't get done. That work is hard and that work is impactful, it gives you a sense of purpose' 4. 'ive cleaned more toilets than all of you combined 💩 🤢 .. you can't show me a task that is beneath me' 5. 'an organization of the past where there's a king 👑 (CEO), then you have the royal subjects/court, then you keep working your way down - eventually you have employees. Well the reason why it was designed that way is because they wanted their soldiers 💂‍♂️ to have as little information as possible because their fundamental purpose of the soldiers is to die in the field of battle. To die without asking questions. I only have 30,000 employees. I would like none of them to die. I would like them to question everything. So the way you organize in the past and the way you organize today is very different' 6. My personal favourite quote from Jensen : 'There are lot of things we don't control, Your job is to make a unique contribution, live a life of purpose, to do something that nobody else in the world would do or can do, to make a unique contribution so that in the event that after you're done, everybody says the world was better because you were here 😇 ' 7. 'I live my life kind of like this, I go forward 🎥 in time and I look backwards 👀 ..and the reason for that is that its easier, I would look backwards and kind of read my history..you figure out what is the end result that you are looking for and you work backwards to achieve it' 8. 'have a core belief, gut check it everyday, pursue it with all your might, pursue it for a very long time, surround yourself with people you love 😍 , and take them on that ride 🏎 ' ps : I learned a lot about generative AI, he broke it down into packets of jargon an ignoramus like me can finally grasp it 😂

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How do we translate and implement #AI in #healthcare? Here, in this latest New England Journal of Medicine AI paper, we outline our journey from "code to clinic" in Singapore, which took nearly 20 years. We first set up a national #telemedicine program in Singapore's primary care clinic system for diabetic retinopathy screening (SiDRP), and then integrated, in a phased approach, a #deeplearning algorithm (SELENA+) to this national telemedicine program. We outline the steps, the lessons learnt, and the challenges faced. We hope this case study is a model for other AI algorithms in other healthcare settings! https://lnkd.in/ge6gXtT2 Dinesh VG Wynne Hsu Mong Li Lee Steven Miller Daniel Ting Gavin Tan Haslina Hamzah Hon Tym Wong Singapore National Eye Centre EyRIS NEJM Group NEJM AI #aihealth #deeplearning #clinicalinnovation #digitalmedicine #telemedicine #diabetes #diabeticretinopathy #medicalresearch #aimedicine #translationalresearch

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Last week, Mayo Clinic announced that Seoul National University Hospital has joined Mayo Clinic Platform_Connect, with the goal of creating the premier global health data network. We wrote down a few thoughts. 1️⃣ 𝐓𝐡𝐢𝐬 𝐢𝐧𝐢𝐭𝐢𝐚𝐭𝐢𝐯𝐞 𝐢𝐬 𝐦𝐚𝐤𝐢𝐧𝐠 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐄𝐇𝐑 𝐩𝐥𝐚𝐲𝐞𝐫𝐬 𝐨𝐛𝐬𝐨𝐥𝐞𝐭𝐞 EHR and MedTech companies have to "give away" their data to fuel the Mayo Clinic Platform_Connect platform and do not have any power on this new data lake, which is fully operated by hospitals. EHRs will be relegated to mere "back-office" databases and excluded from this new value chain. 2️⃣ 𝐇𝐨𝐬𝐩𝐢𝐭𝐚𝐥𝐬 𝐚𝐫𝐞 𝐫𝐞𝐠𝐚𝐢𝐧𝐢𝐧𝐠 𝐜𝐨𝐧𝐭𝐫𝐨𝐥 Historically, hospital IT fell into the category of "low strategic relevance" and was often outsourced. However, over the years, IT and health data have become pivotal to the future of healthcare. Recognizing this fundamental shift, leading hospitals are building vendor-neutral data lakes that integrate with all existing hospital IT systems, including EHRs, MedTech, and more. 3️⃣ 𝐓𝐡𝐢𝐬 𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐝𝐚𝐭𝐚 𝐥𝐚𝐲𝐞𝐫 𝐡𝐚𝐬 𝐭𝐡𝐞 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐭𝐨 𝐛𝐞𝐜𝐨𝐦𝐞 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐢𝐧 𝐭𝐡𝐞 𝐰𝐨𝐫𝐥𝐝. ➡️ Width (# records) ➡️ Depth (# data points per records) ➡️ Spread (diversity of records / data points). This is how John Halamka, the CEO of the Mayo Clinic Platform, defines the quality of a health database. With four of the top 11 hospitals in the world already using its platform, Mayo Clinic is improving daily across these three dimensions This initiative from Mayo is the first of its kind, as it unites (the best) hospitals beyond borders, while most initiatives so far have been very local. 4️⃣ 𝐖𝐡𝐚𝐭'𝐬 𝐢𝐧 𝐢𝐭 𝐟𝐨𝐫 𝐧𝐞𝐰 𝐣𝐨𝐢𝐧𝐞𝐫𝐬? 𝐁𝐞 𝐭𝐡𝐞 𝐌𝐚𝐲𝐨 𝐂𝐥𝐢𝐧𝐢𝐜 𝐨𝐟 𝐭𝐡𝐞𝐢𝐫 𝐫𝐞𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞 𝐜𝐨𝐮𝐧𝐭𝐫𝐲? Is the Mayo Clinic Platform_Connect a new form of American imperialism, or does it empower leading hospitals worldwide to become the "Mayo Clinic of their country"? To be honest, I'm not familiar with the specific terms of new participants. As is often the case, the truth may well lie somewhere "in the middle." ;) 5️⃣ 𝐀𝐭 𝐭𝐡𝐢𝐬 𝐬𝐭𝐚𝐠𝐞, 𝐢𝐭 𝐢𝐬 𝐬𝐭𝐢𝐥𝐥 𝐮𝐧𝐜𝐥𝐞𝐚𝐫 𝐡𝐨𝐰 𝐭𝐡𝐞 𝐡𝐞𝐚𝐥𝐭𝐡 𝐝𝐚𝐭𝐚 𝐬𝐞𝐜𝐭𝐨𝐫 / 𝐦𝐚𝐫𝐤𝐞𝐭 𝐰𝐢𝐥𝐥 𝐜𝐨𝐧𝐬𝐨𝐥𝐢𝐝𝐚𝐭𝐞 Will #Mayo Clinic Platform _Connect be the standard data platform for the healthcare industry? Who will be the winners and losers when health data platforms start to consolidate? Is Tempus (the leading oncology data #platform) a competitor or a partner of Mayo Clinic Platform _Connect? Ultimately, it will come down to speed, trust, and business models. Aggressive monetization of health #data will likely lead to failure. ------- John Halamka, the CEO of the Mayo Clinic Platform, will answer all the open questions at HLTH Europe in June in Amsterdam. Thank you Angel W. Rabinovich for the great discussion on the topic! #healthtech #healthcare

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The FDA’s latest Executive Summary highlights a significant evolution in regulatory thinking for generative AI (#GenAI) devices. While previous guidance addressed AI broadly, this new approach focuses on the unique complexities of GenAI: + Foundation Models: Acknowledges challenges in managing and regulating third-party models that power GenAI, emphasizing the need for transparency and adaptability. + Non-Deterministic Outputs: Spotlights risks like "hallucinations," requiring stricter controls and tailored performance metrics. + Postmarket Monitoring: Proposes new strategies to address GenAI’s continuous learning and real-world variability. This marks a shift toward a more dynamic, lifecycle-based approach to ensure safety. What are the implications for entrepreneurs? Transparency is crucial—entrepreneurs must document their model's design, training data, and performance metrics, even when leveraging third-party foundation models. Narrowly defined use cases are equally important to ensure products are safely and effectively evaluated, mindful of the competing pressure to create applications with broad utility (and market potential). Startups should prioritize robust monitoring systems to track real-world performance, mitigate risks like bias or hallucinations, and maintain consistent outputs across diverse deployments. As always, human-in-the-loop safeguards and transparent, user-centric designs can enhance trust and safety. FDA’s lifecycle approach means compliance doesn’t stop at approval—continuous evaluation, updates, and monitoring will be increasingly expected to keep products aligned with regulatory and patient safety standards. Explore the full document for insights: https://lnkd.in/dXefRaaS #wearenina #healthcaretechnologies Nina Capital

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NPU and Data Privacy in Healthcare: A Game-Changer As AI revolutionizes healthcare, privacy concerns remain a priority. Neural Processing Units (NPUs), optimized for AI tasks, present a breakthrough by enabling local data processing and anonymization, ensuring privacy while delivering faster insights. What is an NPU and Why Does it Matter? NPUs are processors tailored for AI, allowing: • Local Processing: Patient data stays on devices, reducing cloud dependency. • Real-Time Insights: Faster diagnostics and actionable results. • Energy Efficiency: Perfect for portable medical devices and wearables. How NPUs Enhance Privacy in Healthcare 1. On-Device Anonymization: Patient data is anonymized at the source, minimizing risks. 2. Real-Time Monitoring: Wearables securely process and share aggregated health data. 3. Privacy-Safe AI Training: Anonymized datasets power AI innovations without exposing sensitive information. Applications in Healthcare • Medical Imaging: Enhanced diagnostics with privacy-first design. • Remote Monitoring: Secure, continuous care via wearable devices. • Telemedicine: Confidential, real-time patient-provider interactions. • Precision Medicine: Secure use of anonymized data for personalized treatments. Challenges • Integration into existing systems. • High initial costs. • Establishing clear governance for anonymized data use. The Future of Secure Healthcare NPUs balance AI innovation with patient privacy, setting the foundation for efficient and secure healthcare systems. Investing in these technologies is essential for building trust and delivering cutting-edge care. In the age of AI-driven medicine, NPUs are paving the way for a privacy-focused future. Edgar Perez A/Professor Dr. Shohreh Majd Harvey Castro, MD, MBA. Artificial Neural Networks Pudena Health Consulting Co. SanalBee Mustafa Köroğlu

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There appears to be a "Superstar Effect" in healthcare and biomedical AI research right now. A small percentage of publications are truly novel methods contributions that introduce new capabilities or behaviors; whereas a majority of contemporary research publications are focused on implementation science to assess the real-world utility and performance of new methods. This dynamic seems different from prior eras, when the translational infrastructure for implementing novel AI methods was largely unavailable. While methods research often captures more attention and accolades, both types of research are critical – novel methods without implementation science lacks translatability; implementation science without novel methods lacks novelty. If our goal is to invent and deploy transformative AI methods in real-world healthcare and life sciences contexts, we ought to continue encouraging and rewarding stellar implementation science work alongside breakthrough methods development.

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👉🏼 Performance Assessment of GPT 4.0 on the Japanese Medical Licensing Examination 🤓 Hong-Lin Wang 👇🏻 https://lnkd.in/e5zjBAjG 🔍 Focus on data insights: - 🌟 The correct response rate of GPT 4.0 on the Japanese Medical Licensing Examination questions reached 80.4%, indicating a strong ability to parse and respond to complex medical inquiries. - 📊 Significant variations in accuracy were observed across different question difficulty levels and types, highlighting the importance of contextual understanding in AI responses. - 🔍 The Global Quality Scale

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Healthcare Innovation News for the week of Oct 18, 2024: · Healthcare Venture Studio Industry Report released by HDIG and Lawrence, Evans & Co., LLC - information on trends and leaders. HCVS's have become the most efficient innovation model to quickly grow ideas and IP into unicorns. Hospitals and Corporates are partnering, creating or investing into Studios. This leading industry report identifies, clarifies, and provides insights and contacts to every HCVS in the US. Review a copy here https://lnkd.in/g9nGiky5 and subscribe to HDIG for access to all contacts and detailed investments and performance. · GEMMA Biotherapeutics secures up to $100 million in funding · Health2047 (HCVS) Portfolio Company Zing Health Raised $140 Million · Sunbird Bio Secures $14 Million in funding · Purespring Therapeutics Raises $105 Million in Series B Financing for Gene Therapy Treatment of Kidney Diseases · Oshi Health Raises $60 Million for Virtual GI Platform · Parakeet Health Raises $3 Million for Expansion and Development · Pip Care Raises $5 Million in Funding For Surgical Care - The round was led by A1 Health Ventures, with participation from existing investor UPMC Enterprises. · RadiantGraph Receives $11M Series A Round Read about these and all the news https://lnkd.in/g4kp6unx Meet with HDIG team at the follow events: - Oct 16 - McDermott Will & Emery Hospitals and Health Systems Innovation Summit 2024 #HHS24 - Oct 20-23 - HLTH USA Las Vegas NV - Dec 3 - Bamberg Health Innovation Atlanta GA - Jan 13-15 - J.P. Morgan San Francisco HDIG Search/HDIG Partners/HDIG Funds HDIG is an ecosystem to make healthcare innovation more efficient. HDIG Search: a searchable database of hospital healthcare venture, innovation centers, tech transfer offices. It assists you in understanding the landscape of partnerships, performance, and contacts. Early-stage companies use it to find partners and funding for their pilots, or even professional firms or tech companies depending on their needs. HDIG Partners: Consulting & valuable resources for hands on insight, valuation & improvement. HDIG Funds: Capital investment into pilots & start-ups Launched with nearly 10,000 companies, hospitals, & funds, get full access for a special subscription & you can cancel at anytime, this would include building your profile. Learn more about our Acceleration Pilot Program, paid pilots, reverse studio model & other research & services. #healthcareinnovation #hospitalinnovation #innovationcenters #HDIG #venturestudios #startups

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Digital Healthcare Startup Endo Health Secures Pre-Seed Funding from Top-Tier US Investors Korean digital healthcare startup Endo Health, based in Silicon Valley, has secured significant pre-seed investment from prestigious US venture capital firms and renowned angel investors. The funding round, led by Andreessen Horowitz (a16z) and Krew Capital, with additional support from Anne Wojcicki, CEO of 23andMe, marks a major milestone for the company as it prepares […] The post Digital Healthcare Startup Endo Health Secures Pre-Seed Funding from Top-Tier US Investors first appeared on KoreaTechDesk | Korean Startup and Technology News . The post Digital Healthcare Startup Endo Health Secures Pre-Seed Funding from Top-Tier US Investors appeared first on KoreaTechDesk | Korean Startup and Technology News . #koreatech #Tech #koreastartup #KoreaTechnews #Koreastartupnews

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🚨 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗶𝗻 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗔𝗜! 🚨 Can AI truly emulate the complexities of real-world clinical workflows? 𝗠𝗲𝗱𝗖𝗵𝗮𝗶𝗻 is here to transform healthcare AI by introducing a novel benchmark tailored for clinical decision-making (CDM). The Chinese University of Hong Kong, 𝗮𝗻𝗱 Shenzhen University 𝗽𝗿𝗲𝘀𝗲𝗻𝘁: 𝗠𝗲𝗱𝗖𝗵𝗮𝗶𝗻: 𝗔 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗳𝗼𝗿 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 𝗶𝗻 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼𝘀 🩺 What Makes MedChain Special? • 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Integrates patient-specific details for tailored decision-making. • 𝗦𝗲𝗾𝘂𝗲𝗻𝘁𝗶𝗮𝗹𝗶𝘁𝘆: Links decisions across diagnostic stages for realistic workflows. • 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Simulates real doctor-patient dialogues. ✨ 𝗠𝗲𝗱𝗖𝗵𝗮𝗶𝗻-𝗔𝗴𝗲𝗻𝘁 Features: • A multi-agent framework with feedback loops for error correction. • Advanced Retrieval-Augmented Generation (MedCase-RAG) for better decision support. • Seamless adaptability with 12-dimensional structured patient profiles. 🔍 𝗘𝗮𝗿𝗹𝘆 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 MedChain tested 12,163 clinical cases across 19 specialties, with the MedChain-Agent outperforming other systems in handling sequential CDM tasks! 🎧 Podcast Links: YouTube: https://lnkd.in/gFVdTUjH Spotify: https://lnkd.in/gTfZnkkX 📖 Read the full study: https://lnkd.in/gQNhh3uD Follow us for more innovations in healthcare AI and medical research! #MedicalAI #HealthTech #ArtificialIntelligence #ClinicalAI #AIResearch #HealthcareInnovation #LLMs #AIinMedicine

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🚀 𝐀𝐈 𝐍𝐕𝐈𝐃𝐈𝐀 𝐇𝐞𝐚𝐥𝐭𝐜𝐚𝐫𝐞: 𝐔𝐧𝐬𝐭𝐨𝐩𝐩𝐚𝐛𝐥𝐞 𝐃𝐢𝐬𝐫𝐮𝐩𝐭𝐢𝐨𝐧! NVIDIA’s AI technology is reshaping healthcare, driving advancements from drug discovery to diagnostics. Through GPUs and AI platforms, NVIDIA is facilitating faster, more precise solutions that have the potential to transform patient care. The AI Decade is unveiling a significant fusion of technology and healthcare. #AIDecade #HealthcareInnovation #NVIDIA #TechForGood #InvestorDecade

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Understanding the CMS PY2018 Rerun HPMS Memo. Last week, CMS released a Memo titled, "Rerun of Payment Year (PY) 2018 Deadline." This week's HEALS Academy video helps you understand the memo and its data and financial impact on your organization. The memo is crucial for: → Medicare Advantage (MA) Organizations, → PACE Organizations, Medicare-Medicaid Plans, → Cost Contractors, and → Any demonstration plans. These entities need to submit risk adjustment deletes data for the upcoming rerun of Payment Year (PY) 2018. The deadline for submitting all PY 2018 (2017 dates of service) deletions is 8:00 PM ET, Monday, September 30, 2024. → Importance of the Memo: 1. Ensures accurate and timely payments. 2. Mitigates risks of overpayment. 3. Helps in receiving fair and complete payments. → Steps to Take: 1. Review the CMS memo thoroughly. 2. Identify the necessary data deletions for PY 2018. 3. Ensure submissions are completed before the deadline. → Impact on Organizations: Missing the deadline can lead to financial discrepancies and compliance issues. Timely action is essential for maintaining financial integrity and operational efficiency. → Watch the Video: For a detailed walkthrough, watch our video: https://lnkd.in/eH88K9ae Stay informed and proactive by joining our email list: https://lnkd.in/eSK3ZP-u Follow for more updates and share this information with colleagues to ensure everyone is prepared. By understanding and acting on this memo, your organization can navigate the complexities of risk adjustment data submission with confidence. What are you doing to prepare for the PY2018 Overpayment Anything else you would like to learn about it? Comment below. 👤Follow for more content like this. ♻️Repost to share with others.

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Multimodal de-identified medical data lakes are starting to get traction. E.g., South Korea is on the forefront of collecting multimodal medical data (images, reports, and other modalities) from multiple hospitals across the country. This initiative, in no small measure, is the reason why Korean companies like Lunit become leaders in AI-based diagnostics. Lunit software, especially its breast cancer diagnostics, received CE marks and FDA approvals and is now in use in over 3,000 hospitals across the globe. This is the link to the Korean government describing the details and the current status of this initiative (https://lnkd.in/gZ2JidWN – in Korean). It is, in my opinion, high time we followed suit and started to give AI in Healthcare a chance by building multiple multimodal DE-IDENTIFIED medical data lakes to boost the development of highly generalizable AI models with less bias.

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📢 FDA Digital Health Advisory Committee: Regulating Generative AI in Medical Devices. On Nov 20-21, the FDA’s Digital Health Advisory Committee will explore how to regulate Generative AI (GenAI)-enabled devices throughout the Total Product Lifecycle (TPLC). With 950 AI-enabled devices approved, all using "locked" algorithms at the moment, GenAI brings new challenges. Key focus areas: ✅ Premarket Evaluation – Foundational models need safety and effectiveness from the outset. ⚠️ Risk Management – Robust controls are essential for GenAI’s evolving nature, addressing data drift, bias, and unique risks like “hallucinations.” 🔍 Postmarket Monitoring – Ongoing oversight to ensure devices adapt safely in real-world use. 🔒 IEEE UL 2933: This standard supports the FDA’s priorities, providing a framework for trust, privacy, security, and safety across TPLC management. By promoting transparency and traceability, IEEE UL 2933 helps mitigate GenAI’s unique risks while aligning with FDA requirements to protect patient data and ensure device functionality—an essential foundation as GenAI begins to reshape healthcare technology.

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