Isaac Kohane

𝐋𝐋𝐌𝐬 𝐚𝐫𝐞 𝐧𝐨𝐭 𝐫𝐞𝐚𝐝𝐲 𝐭𝐨 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐜𝐨𝐝𝐢𝐧𝐠, 𝐬𝐚𝐲𝐬 𝐌𝐨𝐮𝐧𝐭 𝐒𝐢𝐧𝐚𝐢 𝐬𝐭𝐮𝐝𝐲 Researchers proposed that integrating AI with expert knowledge could automate medical coding to enhance billing accuracy and reduce administrative costs, but they found available large language models vague and error-prone. #healthcareprofessionals #medicalandhealthcare #Healthcareitnews #blsmedicalbilling #womensinhealth #healthcareit #rcm #doctors

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AI meets Rheumatology: ChatGPT and patient response optimization Large language models like ChatGPT, trained on vast text data, are revolutionizing healthcare by understanding and generating human-like language.

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IGHS' own Mike Reid and collaborators at PEPFAR talk about the road ahead for PEPFAR in the Lancet. 1) Treatment interruptions risk undoing progress. 2) Empowering nurses, leveraging AI, and new treatments like long-acting options are vital for the future. 3) Focus on youth engagement, mother-to-child prevention, and key populations to reduce new infections. PEPFAR's mission is clear: sustain gains, accelerate progress, and ensure long-term sustainability. The economic benefits are undeniable, echoing the success of smallpox eradication. #PEPFAR #HIV #GlobalHealth #Sustainability #UCSF https://lnkd.in/eRZXsMww

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Connected Health Collaborative Community (CHcc), co-hosted by the Digital Medicine Society (DiMe) and Consumer Technology Association with UMass Chan Medical School's Program in Digital Medicine as the founding Impact Sponsor, unites a diverse set of stakeholders across consumer electronics, medical devices, and government to reimagine a system and address the fragmentation in connected health across the healthcare system Based on trustworthy data, information, and interventions, we use interdisciplinary expertise, research, and case studies to develop and demonstrate best practices and advance harmonized approaches to speed the ethical, effective, equitable, and safe use of connected health to improve lives - for everyone. 🎉 Learn more about collaborative communities on the FDA website here: https://bit.ly/400924j 🔗 Learn more about CHcc: https://bit.ly/4gFF0ZZ 👏 Thank you to our members working together to address the fragmentation in connected health across the healthcare ecosystem. Consumer Technology Association UMass Chan Medical School Abbott AdaptHealth AdvaMed Alexion Pharmaceuticals, Inc. AstraZeneca Amazon Web Services (AWS) American Nurses Enterprise b.well Connected Health CareSet ChristianaCare FDA Health Advances Allegheny Health Network Intelligent Product Solutions John Hancock Mayo Clinic Mass General Hospital Medical Device Innovation Consortium (MDIC) Medically Home Oracle Sparx Engineering Verily U.S. Department of Veterans Affairs Vivalink Ypsomed AG

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A new publication from Kirk Wyatt and Samuel Volchenboum on #BigData and #AI in #PediatricOncology. They discuss how big data and artificial intelligence can advance pediatric cancer research, current progress and challenges, and how we can separate hype from realistic expectations as this field is transformed by new technology. https://lnkd.in/gwmQFV9N

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✨ So happy health equity getting the attention it deserves in the latest Journal of Clinical Oncology-CCI issue featuring our publication! ✨ In "Future of Cancer Treatment Guidelines: Integrating Real-World Insights for Equitable Cancer Care," Gregory Calip, PharmD, MPH, PhD and I explore how real-world data (RWD) can bridge critical gaps in cancer treatment guidelines, especially for underrepresented populations. 🩺📊 Key Takeaways: 1️⃣ Bridging Gaps: RWD holds promise for making guidelines more inclusive and applicable, but it requires rigorous methodology. 2️⃣ Guideline Evolution: Integrating real-world evidence can drive more personalized, equitable care in oncology. 🔗 https://lnkd.in/eDkakbhE #HealthEquity #Oncology #RealWorldData

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New research by Dr. Karina Eterovic, MSc, PhD, NYS CoQ highlights the importance of germline sequencing for accurate cancer diagnosis and treatment. This approach helps differentiate between tumor-derived mutations and clonal hematopoiesis (CH) mutations, leading to more precise treatment decisions. ➡️ Read the full story: https://lnkd.in/ezM6KXWx #cancer #cancercare #cancerdiagnostics #diagnostics #cancerresearch

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How can genomics revolutionize healthcare? Public health genomics bridges the gap between genetic science and community health, enabling more precise disease prevention, diagnosis, and treatment strategies. By leveraging genetic insights, we’re creating a future where healthcare is more personalized, efficient, and impactful. Let’s explore how genomics is shaping public health and transforming lives worldwide. #PublicHealthGenomics #HealthcareInnovation #Genomics #PrecisionMedicine #FutureOfHealth Link: https://lnkd.in/gHeMrukB

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Read about the stellar science panel from #StateOfPossible24 and what was said about external innovation, finding success in down years, rebooting the immune system, advances in oncology & obesity, and what the panelists think is most exciting right now in the industry. https://lnkd.in/ep5ydWUM If you're a #MassBioMember, you can watch the panel in its entirety on MB Vision: https://lnkd.in/e5UeUPZ5. Abraham (Abe) Ceesay | Emma Lees | Stan Wang, MD, PhD | Jacob Petersen | Chris Garabedian

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This week, on LARVOL Onco Data Podcast, we have a special guest, Wafik S. El-Deiry, MD, PhD, FACP, Director, Legorreta Cancer Center at Brown University who will be in conversation with our host, LARVOL’s Mark Gramling, to discuss the latest trends in Precision Oncology. Tune in on September 7, 2024, at 2:30 PM EDT—you won’t want to miss it! #LARVOL #OncoDataPodcast #Oncology #CancerResearch #PrecisionOncology #MedicalOncology #CancerTreatment #CancerCare #OncologyUpdates #MedicalPodcast

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Tune in now to #CGCAnnual2024 to hear Dr. Robert Sebra from Icahn School of Medicine at Mount Sinai as he discusses the interpretable and context-free deconvolution of multi-scale transcriptomic lung cancer data. In this session we’ll learn: the analytic strategies for spatial transcriptomic data, the algorithms used to deconvolve cell type fractions from the transcriptomic data, the training and validation processes for the machine-learning based deconvolve algorithms, and new findings in the biology of lung cancers by spatial transcriptomic data.

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Researchers are leveraging AI to sift through decades of animal testing data, minimizing the need for new tests. Joseph Manuppello of the Physicians Committee for Responsible Medicine highlights AI's efficiency in extracting and synthesizing this data. Prof. Thomas Hartung of The Johns Hopkins University notes that AI matches or surpasses human accuracy in information extraction. Projects like AnimalGAN and Virtual Second Species are paving the way for AI-driven toxicity testing.  https://lnkd.in/g6t7i-pS #AI #Pharmaceuticals #MedTech #DeepTech #IP #VC #Patents

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Stanford University School of Medicine magazine showcases the rich history of AI at Stanford and highlights many of our faculty members who are at the helm of melding powerful advancements in AI with medicine and health care. The recent buzz around AI isn't new, but excitement is building around use of AI to reveal insights and connections we haven't seen before. "AI can be, in some ways, superhuman because of its ability to link disparate data sources," says AIMI Center Director Curtis Langlotz, commenting on the technology's capabilities. "It can take genomic information and imaging information and potentially find linkages that humans aren't able to make. Sylvia Plevritis, PhD, a professor of biomedical data science and of radiology, is also one of the leaders of the RAISE-Health initiative. She developed a systems biology cancer research program that bridges genomics, biocomputation, imaging and population sciences to decipher properties of cancer progression. "Today, AI is completely changing the way we connect the dots between basic science research and clinical care," said Plevritis, who is in the Stanford Medicine leadership group focusing on what this new path means for medical education. If you're new to #AI, large language models and machine learning, check out AIMI Center Co-Director Dr. Nigam Shah's "AI 101" list of definitions in the story. Visit https://lnkd.in/dHw-TcJt to read more from our Stanford Medicine and AIMI Center experts! Interested in diving deeper? Join us for the upcoming RAISE and AIMI symposiums, May 14 and 15, for in-depth discussions on the pioneering developments in AI that are shaping healthcare! RAISE Symposium - May 14 Time: 8:30 a.m. – 1 p.m. PDT Details and registration: https://lnkd.in/eZWBtMmk AIMI Symposium - May 15 Time: 9 a.m. - 4 p.m. PDT Details and registration: https://lnkd.in/gtjPfiAE #AIMI24 #ResponsibleAI #AIInHealthcare #MachineLearning #AIMIsymposium #RAISEhealth #RAISEhealthSymposium

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Happy AI Friday! You might not be familiar with the predictive model being built at Dana-Farber Cancer Institute called OncoNPC, but it's exciting for humans concerned about cancer. The goal is to train this model across many disparate datasets, including genomic data, to better identify sites of origin for cancers. In an interview with Center for Healthcare Innovation writer David Raths, Dr. Alexander Gusev described their data challenge: "There's a global challenge in academia of patient and clinical data sharing because it is almost always coming from sensitive patient groups, sometimes who have not consented to have their data shared. But even if they have consented to data sharing, they are still always concerned about de-identification with genetic data." By utilizing Duality's Confidential AI solution, which combines Confidential Computing with Federated Learning, Dr. Gusev and the team can move much faster in terms of both attracting and onboarding new data partners (health care providers) as well as analyzing the data from the partners they already have. "Our hope is that from there we can recruit others...that this can work in a plug-and-play way for two hospitals. I think that'll be the practical way to convince people that this can continue to work at a larger number of institutions." Dr Gusev closed by describing the significance of the ready-to-deploy solution by Duality "The ability to move through different levels of security — to either have just a federated approach where nobody has access to anybody else's data, or, on top of that, have a Trusted Execution Environment where even those individual data analyses are done in highly secure environments — that kind of flexibility is something that's pretty unique that I haven't seen from other tools. I think, especially as we try to expand this out to other institutions, they may have additional restrictions that they want to impose on their individual unit, and this software service allows us to do that. So that's also the future-proofing nature of this. If somebody wants something even more secure, we can toggle that on for them. " Read the interview with Dr. Alexander Gusev here: https://lnkd.in/dv52-ERE #oncology #healthcare #realworlddata #dataprivacy #machinelearning #secureAI #confidentialAI #confidentialcomputing #federatedlearning

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Don’t miss the latest episode of The Bio Report podcast, where our CBO Hilary Eaton, PhD joined Daniel Levine for a wide-ranging conversation about the role of #GenerativeAI in drug development, our OpenCRISPR-1 molecule and why we made it open-source. 👉 https://lnkd.in/gkD4iAEt #AI #CRISPR #OpenCRISPR #ProteinDesign #Podcast

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