Rebecca Torrence’s Post

With healthcare AI deals growing twice as fast as in other tech areas, as Rebecca Torrence highlights here, so does the need for high-quality, updated training data. Our team is proud to be at the forefront of solutions that enable AI companies to compliantly and quickly leverage sensitive data. #HealthcareAI #HealthcareData #AI

With minimal regulation around the training of AI models — it’s still kind of the Wild West out there in health AI land. To protect your business and yourself from future legislation, class action lawsuits, civil liability, and criminal prosecution, getting a certification that the training data is in fact legally deidentified under HIPPA and not simply tokenized, hashed or anonymized will be a critical step in minimizing future legislative and legal risks. For more on the differences and cost benefit analysis of simply redacting PHI, anonimizing, or legally deidentifying your assets, HMU and we can help you explore whether you’re opening yourself to risks or not and the right way to insulate the important work you’re doing.

NEW: Healthcare deals are finally picking up again after a funding slump. And those deals — to the relief of many VCs — don't look like they did before the downturn. In 2021, some healthcare startups getting funded had little to no revenue, minimal market traction, or hadn't proved their ability to significantly help patients. Investors have higher standards now, and they're writing smaller checks at lower valuation multiples. But there's one area of healthcare that's making an exception — artificial intelligence. In my latest for Business Insider, here's how healthcare AI deals are bucking the industry's new normal, and what types of healthcare AI startups are bound to get more VC cash: https://lnkd.in/euBSHf4u (Thanks so much to Scott Barclay, Nina Achadjian, Todd Cozzens, Garheng Kong, and Andrew Arruda for these great insights!!)

Hippocratic AI announced the closing of $53 million #SeriesA funding round at a $500 million valuation, bringing total funding to $120 million. The round was co-led by Premji Invest - US  and General Catalyst with additional investment from SVA and Memorial Hermann Health System, as well as existing investors. The company also released today its first product for phase three safety testing: a staffing marketplace for healthcare where health systems, payors, and others can “hire” generative AI agents that complete low-risk, non-diagnostic, patient-facing healthcare tasks to help solve the massive shortage of healthcare nurses, social workers, nutritionists, and other healthcare professionals. This new funding round will support the development and delivery of the world’s first generative AI-powered healthcare agents that can unlock ‘Super-Staffing’ for healthcare and improve outcomes for patients and providers alike. Financial Times Munjal Shah #funding #alert #healthcare #AI #tech #startup #fusion #connectin https://lnkd.in/gq5GkNPt

The relentless surge in AI-driven investments is reshaping the healthcare landscape, with VCs pouring billions into startups that are rapidly outpacing traditional life sciences organizations. This wave of innovation poses a direct threat to established players, underscoring the urgent need for life sciences leaders to aggressively innovate and invest in AI technologies to maintain their competitive edge and relevance. #AIinHealthcare #TechDisruption

Discover how AI is transforming healthcare: Investment in AI-driven healthcare startups surged, eclipsing traditional tech, with a focus on improving efficiency and tackling industry challenges. @SVB_Financial #HealthTech #AIInvestment

💼 𝐇𝐞𝐚𝐥𝐭𝐡 𝐈𝐓 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐫𝐚𝐢𝐬𝐞𝐝 $1 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 𝐢𝐧 𝐐2, signaling the sector's resurgence. 📈 Investments are up from $451.3 million in Q4 2022, with generative AI and remote patient monitoring (RPM) at the forefront. 🤖 Generative AI captures over a quarter of Q2's healthcare IT investments, focusing on efficiency and capacity enhancement. 💰 𝐓𝐨𝐩 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐟𝐮𝐧𝐝𝐢𝐧𝐠: Hippocratic AI's $50 million seed round and Hyro's $20 million Series B. 🏥 RPM startups gain traction, driven by CMS regulatory changes. 💡 HealthSnap and Optimize Health raise millions for remote patient monitoring solutions. 📚 The industry is cautiously exploring generative AI for efficiency and improved patient experiences. 🚀 Predictions include scaling back reimbursement for RPM programs that don't demonstrate patient outcome improvements. #HealthTech #AI #Healthcare #RemoteMonitoring #Investments #DigitalHealth #GenerativeAI

Driving Healthcare Innovation: Tech and AI #Partnerships Tech companies are increasingly partnering with #DigitalHealth ventures leveraging #AI and #GenAI, creating a powerful force for innovation in the healthcare industry. These collaborations combine the agility and creativity of startups with the resources and expertise of #bigtech, driving the development of cutting-edge solutions that have the potential to transform healthcare delivery and patient outcomes. In 2023, 58% of the announced partnerships between Digital Health ventures and Tech companies involve ventures utilizing AI technology, including GenAI. #MedicalDiagnostics emerges as the top cluster for ventures using all types of AI, while #HealthManagementSystems leads in ventures leveraging GenAI technology. Tech’s expertise in cloud computing, #interoperability, and AI is proving invaluable to Digital Health companies, paving the way for groundbreaking advancements in the sector.

Can you hustle your way to an MVP when starting a healthcare AI company? Unlike tech startups, where a Minimum Viable Product (MVP) might be a bare-bones app to solve a specific problem, the bar for an MVP that delivers medical insights (e.g. risk prediction, diagnosis, treatment suggestions, etc.) is set much higher. It's not just about functionality or user interface. The stakes are incredibly high- a flawed model could directly impact patient health. Developing a healthcare AI MVP is a challenging and research-intensive process. It demands more time, investment, and expertise than typical tech MVPs. There's a reason why most startups in this space emerge from hospital and university settings. These environments provide the necessary foundation for developing an MVP through years of research. Another crucial aspect is clinical evidence to demonstrate that the MVP works. Generating this evidence requires rigorous clinical studies, and there simply are no shortcuts to it. I'd love to hear from others in the field. What are your experiences or insights in creating an MVP in healthcare AI? Share your stories in the comments! #artificialintelligence #healthcare #startups

Is it finally AI’s time to shine in healthcare? Healthcare has tried for years (to little avail) to figure out how AI can be used to make work easier and improve patient care. Despite the middling success, Andreessen Horowitz has bet big on healthcare AI startups in the past year, investing in at least four startups and co-leading three funding rounds totaling $328 million. Investment partner Daisy Wolf general partner Vijay Pande at a16z wrote in an August blog post that the VC firm is aware that “the AI hype cycle has hit healthcare before.” But, the two partners wrote, “we’re excited by today’s overlap of data availability, public foundation models, and widespread interest.” Read more: #health #healthcare #artificialintelligence #AI #healthcareAI #a16z