⌨︎Charles Chen

🎬 Matt Damon and 🏈 Colin Kaepernick have invested in it, and so has 💰Andreessen Horowitz... Function Health's executive team has "engineered a first-of-its-kind approach that focuses on prevention and empowerment"—very much in line with what we aimed to achieve with Carebook when we started it over six years ago. Could they be the ones to fulfill their lead investors' prophecy (link at the bottom) and Dr. Eric Topol, MD's premonitions in his books "The Patient Will See You Now" and "Deep Medicine"? They have just secured a $50 million grant. Let's hope this is not another Theranos and that we are truly witnessing the rise of the next generation of direct-to-consumer health companies. These companies will be key players in the "transition from reactive to proactive" health care that the system—and we—desperately need. What do you think? Links: 📝 Investment round press release: https://lnkd.in/eUG87qkf 🔗 Andreessen Horowitz's prophecy: https://lnkd.in/eZATCf4f

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What's been buzzing the loudest for me so far at HLTH Europe? AI, AI, and more AI, of course. Tongues have been tripping over those two letters in every conversation I've had today or listened to including these nuggets: Michael Chen of Nuclera: "Generative AI is wonderful because it brings more hypothesis-making power for the drug discovery researcher. But ultimately, we all know that AI isn't enough. You need to have the power at the wet lab benchtop in order to validate experiments and bring hits and needs into the local trials, and the quality of these hits and leads that ultimately will help the success rates in phase one through three clinical trials, which often don't rear their ugly heads until it's too late." Geraldine O'Keeffe of EQT Group: "There's a huge amount of investment opportunity in terms of AI-, SaaS-based models, in big data and machine learning in diagnostics, precision medicine...delivering the care you need better, faster, cheaper." Karen DeSalvo of Google: "The availability of AI, the ubiquity of it, and just how quickly that is moving [has been significant in the evolution of AI in healthcare]. What I'm hoping now is the next generation of this technology allows us to democratise access to health for people all over the world, and that we can start to do that much more quickly and much more equitably." Chiara Bucciarelli-Ducci, MD, PhD and Marlies Schijven on clinicians' take on AI: "To scale up adoption of AI in healthcare, industry needs to demonstrate to clinicians and healthcare providers the cost effectiveness and cost efficiencies that the technology can bring at every level." "More often than not, we find that AI does work and helps to bring efficiencies, but it also carries risk. So it needs to be properly explained." Agree, disagree, or follow-up comments on these soundbites? #genAI #AIeverywhere #medicalAI #healthtech #digitalhealth #AIfordrugdiscovery #techbio #healthAI #clinicalAI

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Launch announcement 📢 Courtney M. first engaged with Apollo Fractional almost exactly a year ago Fed up with her existing development partner, she was looking for a partner to support and grow her custom community platform she had built for Pharm Techs Only! After many months supporting and bug fixing, she was ready to take her platform to the new level We did a Build vs Buy comparison, and ultimately decided that a customizable off-the-shelf solution was the best investment, at least for the near term We evaluated many platforms, and landed on Higher Logic + Web Scribble for the new community and job board Trying to align product vision with an existing platform can be challenging, especially when working with limited resources. We definitely encountered some unexpected bumps in the road as we worked through the onboarding and started to hit limitations or unexpected quarks 🎢 I think we were told at least 5x that "No one had requested that before".. or "That is not possible, but you can try to accomplish it with custom code" But after a lot of hard work, the MVP version of the new Pharm Techs Only platform is live 🚀 ✔️ New Branding ✔️ Improved User Experience ✔️ More Community Features ✔️ And a roadmap for growth I believe that niche communities and the curation of engaging human experiences will be key factors for the success of startups in the coming years It has been a great experience working closely with Courtney helping to bring her vision of an exclusive platform to support, engage, and grow a global community of #PharmacyTechnicians to new life 🌏 If you know any hard working #pharmtechs or professionals looking to break into the industry, be sure to share this growing community Improved experiences, additional resources, and many more features coming soon... But now it is time to celebrate all of the hard work 🍻 and watch as the community gets to explore and engage on the new platform 🤝 https://lnkd.in/gKd8tNpt #startups #launchday #community

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Science-fiction is inherently speculative. Author George #Orwell of ‘#1984’ predicted concepts such as doublethink, little earbuds and society’s obsession with the black mirror screens that dominate our lives — and according to the BBC, novelist and short story author JG Ballard, of “High-Rise” and “Crash” fame, has predicted the current tool and cultural fixation of #GenerativeAI in the modern society — only he didn’t just speculate them within a story, he is actually one of the first use-cases of a generative AI used in a creative context — Ballard was so fascinated with the growing technological advancement of computers that he used one to compose poems, essentially the precursor to what we have now with ChatGPT. Today, the debate about the creative use of generative AI and its value on creative industries is an extremely fraught and controversial topic, but if controlled in a space that doesn’t replace human labor or try to equate itself to traditional art forms, it is interesting to see what computers can do and how they are creatively limited in comparison. Ballard’s two poems, The Yellow Back Novels and Machine Gun City are generated, and both include notes on how Ballard achieved producing them. Regardless of quality (Ballard himself probably wouldn’t describe these two poems as his best work), it is interesting to see primitive versions of the technology that we utilize on the daily today, and how these moral conversations that concern them would continuously evolve.

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𝐋𝐢𝐚𝐭 𝐏𝐫𝐢𝐦𝐨𝐫 𝐚𝐧𝐝 𝐡𝐞𝐫 𝐭𝐞𝐚𝐦 𝐚𝐫𝐞 𝐭𝐚𝐜𝐤𝐥𝐢𝐧𝐠 𝐚 𝐦𝐚𝐣𝐨𝐫 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐭𝐡𝐚𝐭'𝐬 𝐜𝐨𝐬𝐭𝐢𝐧𝐠 𝐨𝐯𝐞𝐫 $𝟓𝟎𝟎 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 𝐚𝐧𝐧𝐮𝐚𝐥𝐥𝐲 𝐢𝐧 𝐭𝐡𝐞 𝐔.𝐒., 𝐚𝐧𝐝 𝐢𝐭'𝐬 𝐦𝐨𝐬𝐭𝐥𝐲 𝐩𝐫𝐞𝐯𝐞𝐧𝐭𝐚𝐛𝐥𝐞. I recently sat down with Liat, Co-founder and CEO of FeelBetter, a Boston startup that’s creating solutions for polypharmacy, a widespread problem impacting millions of Americans. Polypharmacy is the use of multiple medications by a single individual to manage complicated health conditions. Simply put, polypharmacy causes: ✅ increased risk of bad drug interactions ✅ side effects ✅ medication errors ✅ lower adherence Before FeelBetter, Liat worked at Teva Pharmaceuticals, the largest producer of generics, as VP of Global Portfolio for Generic Medicines. During her time there, Liat saw patients struggling to juggle large bags of medications, a challenge she personally faced when dealing with her own health issues. She knew there had to be a way to use tech to help healthcare workers reduce the downsides of polypharmacy, and she searched for solutions but found nothing. But her search led to cofounder Yoram Hordan, CTO and COO of FeelBetter, and together they launched the company. 𝐋𝐢𝐚𝐭 𝐚𝐧𝐝 𝐘𝐨𝐫𝐚𝐦 𝐫𝐚𝐢𝐬𝐞𝐝 $𝟏𝟎.𝟓 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐚𝐧𝐝 𝐚𝐬𝐬𝐞𝐦𝐛𝐥𝐞𝐝 𝐚 𝐭𝐞𝐚𝐦 𝐨𝐟 𝟏𝟕 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐭𝐨 𝐬𝐲𝐧𝐭𝐡𝐞𝐬𝐢𝐳𝐞: 🔍 pharmacology data 🔍 health status 🔍 medical history 🔍 clinical guidelines 🔍 evidence-based medicine. FeelBetter uses AI to analyze all this data and give clinicians actionable insights to reduce negative effects of polypharmacy. FeelBetter also identifies at-risk patients and gaps in care in order to enhance well-being and outcomes. A study conducted with Mass General Brigham showed that FeelBetter could predict which patients would require hospitalization based on medication combinations, highlighting the platform's potential to impact care and outcomes. The company was started in Israel where there is comprehensive access to patient data, and it's now expanding across the US and collaborating closely with Medicare Advantage programs, Mass General, Atlantic Health, and senior care facilities nationwide. Connect with Liat Primor to learn more. And be sure to subscribe to Tribe newsletter for the full story. #innovation #management #technology

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Are you working with #Llama3 in #Healthcare? Today John Snow Labs open-sourced this fine-tuned model, which is now the #1 #OpenSource model on the #Medical #LLM leaderboard: https://lnkd.in/gtwXeACW #healthcareai #healthai #ai #generativeai #datascience #largelanguagemodels #research

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Great article by Jesse - I would suggest part of the challenge is that the Internet is big, marketing is hard, and biotech software is (relatively) niche. These are tough problems to overcome no matter how many venture dollars you raise. While I'm sure the Deep Origin and Nitro Bio folks who are linked from the article tried to include as many companies and products as they could in their lists, PipeBio and Enpicom are missing under "-Omics Datasets"; RSpace, eLabFTW, and other members of the ELN Consortium are missing under "ELN"; StackWave's Affinity is missing under ELN, LIMS, Experiment/Protocol Design, Lab Inventory, and Visualization; and our LabInspector software is missing under LabOps.

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Thanks Joanne Chen and Jaya G. from Foundation Capital for the nod! Great to be in the cohort of top notch AI companies. Observability data is untapped goldmine of information, but when the time comes (in the middle of incident), it still requires "expert" skills to find the needle in the haystack. We at Deductive AI are democratizing the expertise to everyone in the organization.

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My thoughts on GPT-4o: Not consequential for the immediate future, as in, This was not a launch that will get a bunch of developers super excited and moving over to the new model for most applications. However, I think it will be hugely consequential for the big picture of how we interact with AI. The extremely believable tones, "emotions" and voices are a gigantic step in allowing us to interact with AI without feeling like it's an alien or robot. More thoughts to come.

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I built a simple web app for to-do lists! I actually built quite a few web apps in the last year - namely using Streamlit to avoid learning how to do front-end development. However, I figured it's time to learn it so I can customize the end-user experience a bit more, but also wanted to figure out the following: 1. Learn a Python framework for web apps - Flask, Django, or FastAPI 2. Learn the minimum set of requirements to deploy a web app, end-to-end, so it's accessible publicly 3. Learn how to deploy web apps on Google Cloud Surprisingly, it wasn't very difficult. Some highlights: 1. I chose FastAPI as my framework because it seems to be the cool kid on the block with its super-fast performance, but also because of its swagger docs that are generated automatically. It took about 20 minutes to write the todo web app using FastAPI. 2. I used Jinja templates with FastAPI for my front-end. Super basic, nothing fancy. Took another 10 minutes to figure that out. 3. I deployed the web app locally, just to test it out. Found some bugs and learned more about local deployment of these apps. Spent another 15 minutes here. 4. I created a new project on Google Cloud and used their App Engine cloud service to deploy my web app. Setup took around 10 minutes. Fairly straightforward using their SDK. 5. Embedded the functioning web app to my personal website to make the URLs easier to navigate. Things are always harder until you actually try it. I avoided this for awhile because there was so much technical jargon I just didn't understand. If you've been wanting to learn something new, but afraid to try it out, take this as a sign to go for it! It's easier than you might think! Here's the link to my to-do list web app https://lnkd.in/e_6iztQN. It's accessible to everyone and everyone will see each other's tasks. You can find all the code for this simple app at OpenClinTech: https://lnkd.in/eB_vTbzD. Happy coding! #healthcareonlinkedin #webapp #coding #fastapi #cloudservices

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In dozens of CXBR reviews at Amazon , I commonly asked a simple question - “how much work is this on the user”. Then faced with silence, I’d reply with let’s count - count the clicks/taps, pageloads…. Work backwards from the customer- Make it easy to use your store. Rule 37- eliminate steps & inputs, if you can’t eliminate: automate, if you can’t automate: make it cheaper and smarter ( delegate & suggest). #usability #ux #workingbackwards

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Everyone seems to want to emulate Kaiser as the go-to model for how healthcare works But almost no one has actually managed to pull off the payer provider combination that Kaiser has. Even Kaiser itself struggled in areas outside of California. I'd be curious what others think is the main reason, but the two big ones IMO 1) You need to command a critical mass of patient lives to be able to pull off exclusive contracts with other physician practices/medical groups in a given geography. Kaiser pulled this off by getting basically all the shipyard workers in California in WWII and used it to its advantage. Other companies have not quite been able to do that. 2) You need to build your internal workflows around the idea that you're taking on financial risk of everyone that comes through your doors. That means way more protocolized care and also getting patients to try cheaper options when medically appropriate. Most hospitals do not operate like this and try to tack on an insurance plan without changing their workflows - in the healthcare 101 course (starts in 1 week), we talk a bit about how Kaiser works and why it's different from other health systems You can sign up for it here: https://lnkd.in/eKycDuTV

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"The perfect AI tool for Medical Information teams doesn't exis..." Actually, yeah it does 😃 We launched medchat-qa to make life super easy for medical information teams 🔬 and it is basically the coolest AI tool for you folks 😎 Because apart from generating volumes and volumes of data in minutes, it's super-powered with: ✅ 18M+ publications ✅ ~500K clinical trials ✅ 20K+ FDA labels ✅ 5000+ news sources Oops, we did a really awesome thing 🤷🏽‍♂️ P.S. If you haven't checked it out already, you totally should because this 👇🏽 is literally how easy we've made it for you 🤯

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#Healthcare #NLP & #LLM 5.3 from John Snow Labs has task-specific language models for extracting #SocialDeterminantsOfHealth from free-text records, including putting them in context (positive / negative / hypothetical assertions, present / past / future, patient vs. someone else): Live demo: https://lnkd.in/emXJNRyA #generativeai #ai #datascience #healthai #healthcareai #sdoh #medicallanguagemodels

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Sometimes we overcomplicate technology just to chase trends. While everyone is talking about AI, ML, and LLMs, one thing you should be aware of is that creating an LLM isn’t easy and certainly not inexpensive. In the meantime, remember the value of good ol' small data and how it can help your business right now! Here’s how embracing a small data-driven culture can transform your gym: Informed Decision Making 💡 Utilise data to make smarter decisions about everything from class schedules to equipment investments. This ensures you’re meeting member needs efficiently. Personalised Member Experiences 📝 Data helps create tailored fitness plans and personalised interactions, making each member feel valued and understood. Enhanced Member Retention 💪 Predictive analytics can identify at-risk members, allowing you to intervene with targeted retention strategies before they consider leaving. Optimised Operations 🏢 Track equipment usage, facility maintenance, and energy consumption to streamline operations and reduce costs, providing a better experience for everyone. Performance Tracking 📈 Monitor and analyse the performance of classes, trainers, and overall member engagement to continuously improve your offerings. Marketing Insights 🎯 Leverage data to understand member demographics and preferences, tailoring marketing campaigns to attract and retain the right audience. Continuous Improvement 🚀 A small data-driven culture promotes a cycle of continuous improvement, where feedback and results are regularly analysed to enhance services and operations. By fostering a small data-driven culture, fitness operators can become more responsive, efficient, and member-focused. Harness the power of small data for sustained business success! 🌟 #FitnessTech #DataDriven #GymInnovation #MemberExperience #SmartGyms #FitnessCommunity #GymLife #ContinuousImprovement

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RAG is all the rage This TechCrunch article does a nice job describing what retrieval augmented generation (RAG) is, its benefits and shortcomings https://lnkd.in/et4WFjvq #ai #artificialIntelligence #hallucination #RAG

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