Steffen Vogler’s Post

📢 IT Partnerships Share-Out: Updates from Bayer & MIT CSAIL!   I’m thrilled to share key takeaways from the recent 'Tech Talk' at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) presented by my esteemed colleague, Dr. Steffen Vogler. Thank you to Christiana K. for hosting us!   During the session, Steffen highlighted the crucial intersection of AI and healthcare, emphasizing the need for a data-centric approach to machine learning. He introduced "Croissant" (https://lnkd.in/egd2r85F), a standardized metadata format that is developed as an open-source tool under the supervision of MLCommons and that has the potential to improve quality of data exchange in Healthcare.   Here are some key points from the talk: 1. Addressing Healthcare Challenges: With radiology facing increased demand and a shortage of healthcare professionals, leveraging data-driven AI solutions is essential. Steffen pointed out that improving data practices today can lead to better patient outcomes tomorrow. 2. The Power of Data-Centric Machine Learning: Rather than focusing solely on model architecture, we must prioritize the quality and structure of input data to create reliable AI systems. 3. Introducing Croissant: This innovative tool is designed to enhance ML-readiness of datasets, which facilitates clearer data exchanges among researchers and enhances discoverability. 4. Collaborative Efforts: To be fully effective, Croissant needs to be supported and embedded by an ecosystem of data providers, technology enablers, and innovators. The ecosystems can either be fully open or, if intended for patient data, secured and protected such as Bayer’s new AI Innovation Platform.   Our ongoing collaboration with MIT CSAIL underscores Bayer's commitment to advancing healthcare through innovative technology, and we are excited about the potential of projects like Croissant to transform the medical landscape.   Let’s continue to push the boundaries of what's possible in healthcare, utilizing AI responsibly and effectively!   #AI #Healthcare #TeamBayer #MITCSAIL #DataCentric #Innovation #Collaboration #BayerInRadiology #SeeThePossibleCreateTheFuture #LifeScience #HealthForAll #HungerForNone #Partnerships Bijoy Sagar, Dr. Matthias Vennemann, Mark Sparks, Markus Blank

After a successful Day 1 at The Alliance for Artificial Intelligence in Healthcare (AAIH) Annual Member Meeting, it is time for a recap! - Ashley Magargee shared her views about the promise of AI in Healthcare and examples across Genentech / Roche where AI is making an impact. - Daniel Kraft, MD (with help from AI Daniel) takes about AI advances and applications in healthcare. - Dan Sheeran (he/him) shared concrete examples where AWS is partnering with healthcare organizations to deliver value - Pranava Goundan (ZS) shared the benchmark ZS conducted across 20+ Life Sciences companies and AI use cases across all phases of the hype cycle. - Ali Alemozafar (Wilson Sonsini) discussed considerations when generating IP through AI: “Have human in the loop; IP generated only by AI is not patentable.” - Panel: From Concept to Cure discussed some key takeaways including: --> Working with the FDA - “we are the bottleneck” --> Focus on data - “if you want to leapfrog the competition, do the foundation right.” --> Skillsets of the future - may need a “new breed of scientists” - Poster Sessions were conducted, featuring innovative work with AI in healthcare, from drug discovery, to clinical to legal. Stay tuned for a recap of Day 2, and let us know what your key takeaways from Day 1 were! #AAIH #annualmembermeeting #aaihannualmembermeeting

With the upcoming webinar, “Medical, reimagined: How technology-driven insights can help us rethink strategy and execution,” featuring Jim Streeter - Envision's President of Technology and Chief Technology Officer, just days away, we're re-sharing one of our most popular blogs from 2024 - Jim's insights on how data and AI are transforming the life sciences industry! Find the full text here ➡ https://lnkd.in/dNGnYM5J, or check out key insights below! At Envision Pharma Group, we understand the importance of integrating historical, predictive, and generative AI to streamline workflows and enhance decision-making for medical affairs professionals.   Key Insights: ✅ Humanizing Data: Making data accessible and intuitive for all stakeholders is crucial. By integrating various AI technologies into a single platform, we minimize the need for life sciences professionals to switch between different systems, enhancing efficiency and effectiveness. ✅ Addressing Data Challenges: Quality, privacy, and standardization are critical when dealing with extensive historical data. Our approach involves using advanced algorithms to clean and standardize data while ensuring privacy through meticulous anonymization processes. ✅A Collaborative Future: We emphasize the need for data standardization and open APIs to foster a more collaborative ecosystem in the life sciences industry. This approach simplifies processes and improves decision-making across medical communications and drug development.   #Webinar #MedicalAffairs #DatainLifeSciences #AI 

This May, we were delighted to conclude another cohort of our AI course. The course, launched three months ago, was designed for clinicians, researchers, innovators, and managers interested in exploring data and artificial intelligence. Our goal was for participants to identify AI opportunities in their practice, understand the unique challenges of medical data, and connect with Clalit experts who can help move projects from feasibility studies to implementation in healthcare. Towards the end of the course, participants were invited to submit proposals for an "AI Challenge," where ideas that can be solved using data and AI were scored. Over 40 proposals were submitted this year, and 4 made it to the finals. First place went to Dr. Sharon Hovav, Moria Amgar, Shiri Kfir, Ilya Levner, and Avital Saranga from the Logistics and Infrastructure Division, with their project: "From Supply Chain to Treatment Continuity - Ensuring Medication Availability for Patients." Congratulations to the winners! We thank all participants who submitted challenges and encourage you to continue exploring data and AI-based solutions to advance healthcare. Stay tuned for announcements about the next cohort! #aihealth #aichallenge #healthai #aiinnovation #innovation #healthcare #healthcareinnovation #healthcarechallenge #winners #healthtech #medtech

🚀 At #aiPulse last week organized by Scaleway, I had the pleasure of moderating a panel on the challenges of scaling AI in #HealthTech and #BioTech with: Julia Gimbernat Mayol of InstaDeep Jean-Philippe Vert of Bioptimus Robert Marino of Qubit Pharmaceuticals 🏥 AI in healthcare offers groundbreaking potential but comes with unique challenges. Here are 4 key takeaways from our discussion: 1️⃣ Data Complexity & Access: From protected medical data to scarce experimental datasets, accessibility remains a critical barrier, demanding innovative partnerships and synthetic data solutions. 2️⃣ Deep Understanding: Accurate models require a nuanced understanding of data generation methods, essential for robust and reliable AI outputs. 3️⃣ Adapting AI Architectures: Custom multimodal AI models and engineering innovations like model sharding are reshaping how biological data is analyzed. 4️⃣ User Adoption: Even the most advanced AI tools must be accessible and user-friendly, empowering healthcare professionals to meaningfully leverage their capabilities. 🗞 Link to the story in the comments 👇 🗣 Mayol said that while it's great to build general models, InstaDeep is always seeking to identify high-value use cases. To do that, the company spends a lot of time trying to talk to end users and trying to understand their challenges in working with these tools:

With the EU AI Act coming soon, be great to understand the use cases for us in the industry right now and in the near future….

I had the privilege of moderating a webinar on AI in health care with international leaders representing the perspectives of regulators, care delivery systems and industry / developers of AI technologies. The panelists were Khang Nguyen, Chief Clinical Transformation Officer at SOUTHERN CALIFORNIA PERMANENTE MEDICAL GROUP, David Rhew, M.D. Global CMO at Microsoft Health, and Erick Lin, MD, PhD, MBA - Medical Officer at the FDA. In our wide-ranging conversation, a few takeaways: 1) we discussed the importance (and dearth) of high quality evidence to demonstrate safety and effectiveness of AI tools (and whether the FDA's bar for evidence is too low); 2) the potential of using AI to empower patients to better self-manage their care (with guardrails) 3) the work of collaborative efforts like TRAIN - to develop technology solutions to enable responsible AI programs at health systems of all sizes. If you didn't get a chance to attend the webinar, I'm happy to share a recording of the conversation here ⬇ https://lnkd.in/gb3xDBbB Kudos to Karin Cooke, Vivian Tan and the excellent team at Kaiser Permanente International for hosting this important conversation.

Last week, we shared the exciting news that the Biofourmis Connect life science platform is now part of ActiGraph’s Digital Health Technology ecosystem! You can check out our updated website for more information - ➡️ https://hubs.la/Q032tjDN0 Learn more about how to unlock the potential of big data and AI with a device-agnostic, decentralized trial platform backed by ActiGraph’s proven operational, scientific, and regulatory expertise. With this new combined solution, we look forward to empowering your clinical development team with streamlined collection of continuous, high precision data centered on the patient. #ActiGraph #BiofourmisConnect #DigitalHealth #DrugDevelopment #ClinicalTrials #AI #BigData

🚀 Step into the Future of Clinical Research with SclinEDC, powered by AI! 🧠 🌟 In the dynamic landscape of clinical research, efficiency and accuracy are paramount. With SclinEDC's AI-driven platform, we're revolutionizing the way data is managed, ensuring cleaner data, efficient processes, and faster access to critical information. 🔍 Cleaner Data: Bid farewell to data clutter and inaccuracies! SclinEDC harnesses the power of AI algorithms to intelligently clean and validate data, ensuring that your research insights are built on a solid foundation of clean, reliable data. ⚙️ Efficient Processes: Time is of the essence in clinical research, and SclinEDC's AI capabilities are here to optimize every step of the process. From automated study setup to predictive analytics, our platform streamlines workflows, saving you valuable time and resources. ⏩ Faster Access to Data: In today's fast-paced world, quick access to data can make all the difference. SclinEDC's AI engine provides instant access to real-time data insights, empowering you to make informed decisions swiftly and confidently. Join us as we harness the power of AI to usher in a new era of clinical research, where efficiency, accuracy, and innovation reign supreme. Step into the future with SclinEDC today! Call : 1800 203 5024 email: shyam@sclintech.com #ClinicalResearch #AI #DataManagement #SclinEDC #Efficiency #Innovation #ClinicalResearch #HealthcareInnovation #AIRevolution #AIinClinicalTrials #HealthTech #ClinicalTrials #ClinicalDataManagement #EDCSoftware #AIApplications #MachineLearning #DataAnalytics #ClinicalResearch #HealthcareInnovation #Biotech #Pharma #ClinicalTrialSolutions #DigitalHealth #AIAdvancements #LinkedInPost #Networking #Innovation #ResearchAndDevelopment #LifeSciences #ClinicalOperations #DataQuality #PredictiveAnalytics

To actually gain value from your AI model, it needs to be deployed and actively used in production, which is where MLOps (Machine Learning Operations) comes into play. MLOps bridges the gap between data science and IT, by efficiently deploying, monitoring, and maintaining your model over time.