Kevin Fumai’s Post

Flatiron is uniquely positioned to apply #AI and #machinelearning to advance point of care, #clinicalresearch, and #realworldevidence generation. From extracting clinically relevant information from the EHR, to understanding how treatments work in diverse populations, to surfacing eligible patients for #clinicaltrials, Flatiron has pioneered the use of ML in real-world evidence generation to help us deliver on our mission to improve and extend lives by learning form every person with cancer. ⏯️ Hear from Flatiron Chief of AI, Will Shapiro on a recent episode of the 'What's up with Tech?' podcast.

What if the power to transform healthcare lay in the very data we've been collecting all along? Join us for an illuminating conversation with Will Shapiro, the Chief of AI and Data Science at Flatiron Health, as he shares his remarkable journey from music recommendation systems to the vanguard of personalized medicine. Will unpacks how Flatiron Health is reshaping cancer research and patient care through machine learning and an unwavering focus on personalization. By tapping into vast amounts of patient data, the company aims to enhance cancer care by learning from each patient's experience, offering insights into his inspiring career path that underscores a commitment to change through technology. Explore the transformative role of AI in healthcare, particularly when leveraging real-world data to surpass traditional clinical trial limitations. This wealth of information provides a more nuanced understanding of patient populations, allowing for personalized medicine that considers diverse elements like comorbidities and lifestyle. Throughout our discussion, we stress the importance of validating AI models to navigate challenges like model hallucination and highlight the critical value of data privacy and consent. Will shares how AI is making strides in cancer care by identifying suitable candidates for clinical trials, effectively broadening access to pioneering treatments. As our conversation unfolds, we delve into the significance of collaboration in healthcare AI, spotlighting strategic partnerships with leading tech companies and academic institutions. Will expresses his enthusiasm for the potential of large language models in revolutionizing data extraction from unstructured documents. We also debate the merits of specialized healthcare-trained models versus using general models, as well as the exciting prospects of emerging technologies like agentic design and digital twins. #AI #Healthcare #Cancer #Healthtech #digitalhealth Irma Rastegayeva✨Influence Through Storytelling™️ eViRa Health

The Unseen Bias in Healthcare AI 🤔 Coming from a family in the healthcare sector that always loved technology, I’ve seen firsthand how tech can transform patient care—but only if the physician knows how to use it. The same holds for AI today. ➕ AI is amazing -> It is helping clinicians diagnose breast cancer, read X-rays, and predict which patients need more care. The Nobel Prize in Chemistry, announced today, recognized the work of three researchers: David Baker, Demis Hassabis, and John M. Jumper. They used AI to study and create new proteins. Demis, one of the three, was one of the founders of the company Google DeepMind, which focuses on the use of artificial intelligence in healthcare, studying DNA, new molecules, and more. ⚠️ However, AI risks perpetuating racial biases if trained on historical, inequitable data. An algorithm predicting healthcare needs based on spending patterns was found to recommend less care for Black patients due to historically lower healthcare spending. https://lnkd.in/eeRvFk95 🚨 Early warning signs of heart disease might be missed in female patients because the data used to train these models often skews toward male patterns. Diverse data, transparency, and ongoing monitoring are critical to ensure AI helps all patients fairly and responsibly, as Yale School of Medicine points out. https://lnkd.in/ev7zieXq What other challenges do you see for AI in this or other industries? 💬👇 #HealthcareAI #BiasInTech #DataEthics #InclusiveHealthcare #AIinMedicine #HealthInnovation #ResponsibleAI #TechForGood #HealthcareInnovation #MachineLearning #ProductManagement #Mccombs #UT #Fuqua #Duke

🌟 Transforming Infant Healthcare with AI ? 🌟 At Chelonia Applied Science, we are continuously exploring the frontiers of healthcare innovation. A recent review in #Frontiers in Digital Health underscores a critical area of our interest—applying AI learning to revolutionize infant disease detection and prediction. 👶 Why It Matters: Early diagnosis in infants can change lives. AI’s capability to analyze vast datasets from clinical and demographic information offers unprecedented precision in detecting conditions during the most vulnerable first year of life. 🔬 Research Insights: Between 2018 and 2022, studies leveraging AI for infant healthcare have shown promising growth. Techniques like deep neural networks have become increasingly popular, although traditional methods still hold significant value, particularly in data-constrained environments. 💡 Chelonia’s Vision: We believe in harnessing the power of AI to not only advance infant health but also to accelerate drug discovery processes. Our commitment is to integrate these technologies to develop solutions that are not just innovative but also ethical and sustainable. 🤖 Looking Ahead: The continuous advancements in AI provide a robust foundation for developing tools that could soon be standard in clinical settings, enhancing diagnostic procedures and ensuring better outcomes for our youngest patients. 👉 Follow us on LinkedIn and X 📫 Register to our newsletter (issued no more than 5 times per year) https://lnkd.in/e8JxcBdF Join us as we continue to push the boundaries of what's possible in healthcare and drug discovery. The future is here, and it’s digital! #CheloniaSwiss #HealthcareInnovation #AIinHealthcare #DigitalHealth #DrugDiscovery #InfantHealth #MachineLearning

Experts in healthcare innovation gathered at the Penn LDI AI in Health Care Conference to explore the transformative potential—and urgent challenges—of generative AI in clinical settings. Key topics included AI’s role in improving diagnostics and personalizing treatments, along with the need for transparency, fairness, and strong regulatory frameworks. Hamsa Bastani, faculty co-lead of the Wharton Healthcare Analytics Lab, emphasized the importance of rigorous testing to mitigate bias and ensure AI applications truly enhance patient outcomes. As healthcare rapidly evolves, these discussions underscore the essential balance between innovation and ethical responsibility. Read more about the conference's takeaways here: https://lnkd.in/gzbKYMNv Leonard Davis Institute of Health Economics (Penn LDI) #PennAI #WhartonAI

🚀 Excited to share key insights from our recent publication in Radiography: "A Nordic Survey on Artificial Intelligence in the Radiography Profession – Is the Profession Ready for a Culture Change?" 🔍 Key Highlights: Positive reception: A majority of Nordic radiographers are optimistic about the integration of AI in radiography, with 77.9% viewing it as a positive influence on the profession. This enthusiasm underscores the potential for AI to transform radiographic practices by enhancing diagnostic accuracy and workflow efficiency. Implementation readiness: While there is strong support, our survey revealed crucial gaps in AI knowledge and training among professionals. Addressing these gaps is essential for the responsible adoption of AI technologies in clinical settings. Cultural insights: Using Edgar Schein's model of organizational culture, our study delved into the profession's cultural readiness for AI. We identified a blend of excitement and concern, highlighting the need for a careful balance between technological advancement and maintaining the human touch in patient care. 🔗 https://lnkd.in/dFQBwDnp 👥 A huge thank you to all survey participants and my co-authors for their invaluable contributions to this important discussion. As we navigate these changes, let's continue to focus on enhancing patient care through innovation and education. #Radiography #ArtificialIntelligence #HealthcareInnovation #ProfessionalDevelopment Malene Roland Vils Pedersen Janni Jensen Martin Weber Kusk Helene Mork-Knudsen Dr Christina Malamateniou, Reader/Associate Professor

🔔 Join Us for an Exciting Webinar: A Conversation – AI in Clinical Research 📅 Date: 14th November 2024 🔗 Register now and secure your spot! ➡️ https://lnkd.in/gK8bdtdx This session will feature a panel of distinguished speakers who will delve into the application of artificial intelligence in clinical research space, sharing their invaluable insights, best practices, and emerging trends. What to Expect: 🌐 Understand foundational AI and its relevance in clinical research 🏥 Discover the importance of AI in transforming patient recruitment and site management 📊 Learn how to leverage AI and data analytics to support, enhance, and add value to clinical research ⚖️ Explore challenges, opportunities, and other considerations 🔍 Stay updated on emerging trends and risk-based approaches And much more! Don’t miss this opportunity to gain valuable knowledge from industry experts. Tam C. Nguyen Shigeto M. Bhargava Krishna Sreepathi, PhD, MBA Serena Chan David Gebbo 🔗 Register now and secure your spot! https://lnkd.in/gK8bdtdx

Perceiving everything that changed over a 12-month period is a rough task as we focus more on negative events than positive ones. So I asked to a ML system to give me a rewind of the past year (through my LinkedIn activity). - Copied as is. Here's my 2024 LinkedIn Rewind, by Coauthor.studio: 2024: The Year AI Became More Than Code - It Became a Healthcare Ally 🚀 This year taught me that the most powerful AI doesn't just process data—it transforms lives. My journey from pure research to real-world medical diagnostics at Unilabs proved that technical excellence and human impact are two sides of the same coin. Some highlights that redefined my understanding of AI's potential: - Honored to receive the European Association for Biometrics Max Snijder Award, recognizing our work in explainable AI. This wasn't just a personal milestone, but a testament to making AI systems more transparent and trustworthy. https://lnkd.in/dDbV8Dwg - Joined Unilabs as an AI Scientist, where we're not just developing algorithms, but building tools that could fundamentally change medical diagnostics. We're trying to push the boundaries of what's possible in radiology, pathology, and genetic analysis. https://lnkd.in/dvwcmdw2 - Published three groundbreaking papers at ECCV 2024 Workshops, exploring fairness in facial recognition, knowledge distillation, and synthetic data challenges. Each paper is a step towards more ethical, reliable AI systems. https://lnkd.in/d-pqW4Cw Additional milestones that kept me inspired: - Ranked in the top 5 at the FRCSyn Challenge at CVPR 2024 - Published critical research on colorectal cancer diagnosis using deep learning - Continued teaching at FEUP, ensuring the next generation of AI researchers thinks beyond code Looking ahead to 2025, I'm committed to bridging research and real-world application. Our goal isn't just technical innovation, but creating AI that genuinely serves human needs. A massive thank you to my incredible collaborators, mentors, and the entire research community who make this journey possible. Together, we're not just developing technology—we're reimagining healthcare. #AIinHealthcare #ExplainableAI #LinkedInRewind #Coauthor #2024wrapped -- Get your 2024 LinkedIn Rewind! Go to coauthor.studio

👉🏼 Workshop summaries from the 2024 Voice AI Symposium, presented by the Bridge2AI-Voice Consortium 🤓 Ruth Bahr 👇🏻 https://lnkd.in/exJrTbzM 🔍 Focus on data insights: - 📊 International standards proposed to unify stakeholders in vocal biomarker research. - 💻 Practical deployment challenges of AI solutions identified, revealing gaps between laboratory and real-world applications. - 🗣️ Innovations shared in ethical AI practices and advanced voice dataset collection techniques. 💡 Main outcomes and implications: - 🌐 Successful integration of AI in health applications highlighted, indicating significant advancements in voice signal analysis. - 🔒 Emphasis on data privacy and clinical validation processes essential for future implementations of voice-based AI tools. - 🧠 Interdisciplinary collaboration deemed crucial for overcoming technical and ethical challenges in voice biomarker research. 📚 Field significance: - ⚙️ Establishing robust data collection standards will enhance the reliability of AI models in healthcare diagnostics. - 🌱 Future innovations in AI-driven voice analysis are likely to improve treatment options for individuals with voice disorders. - 🛠️ The symposium provided a foundation for ongoing collaboration between academics, clinicians, and technologists, fostering growth in the field. 🗄️: [#VoiceAI #Biomarkers #DataInsights #HealthcareAI #InterdisciplinaryCollaboration #EthicalAI #VoiceDisorders #MachineLearning #DataPrivacy]

Can we trust #health #AI to be #safe and #effective? 🤔 Join me for part 2 of ieso's #DemystifyingAI webinar series this Thursday! 🌍At ORCHA, we work with #healthcare providers across the world to bring safe, effective #healthapps to their patients using our #healthapplibraries and #digitalformularies. 🔍Many of these direct-to-consumer products are incorporating AI-powered features but navigating 'What Good Looks Like' when it comes to #Evidence and #ClinicalSafety is difficult, especially for busy #healthcareprofessionals. I'm looking forward to sharing my perspective on this topic, highlighting the regulatory gaps and key considerations when choosing or using your next #AI health technology. #healthtech #healthinnovation #digitalmentalhealth #healthcareleadership #medtech