Mathias Goyen, Prof. Dr.med.’s Post

digital health: radiology: AI: Artificial Intelligence: #RSNA2024

🎓Almost Two Months in Boston for My MPH at Harvard T.H. Chan School of Public Health. It’s been an incredible journey so far. Here are some highlights: -Education in the AI Era, Precision Medicine 2024: In October, I had the chance to attend this thought-provoking event organized by Harvard Medical School Department of Biomedical Informatics. The highlight was undoubtedly the debate between Isaac Kohane and Peter Szolovits on a topic that’s on many of our minds: Should GPT-4 Write My Thesis? (https://lnkd.in/dqii487g). It was a fascinating conversation that challenged our views on AI’s evolving role in academia. -Harvard I-Lab: Joining the Harvard Innovation Labs has expanded my perspective on AI in healthcare beyond research to encompass an entrepreneurial mindset. Listening to Jorge Cortell’s story about bootstrapping a unicorn was particularly inspiring. The i-Lab offers unparalleled opportunities, such as 1-on-1 mentorship sessions with successful entrepreneurs like Jorge, which help bring big ideas within reach. Being around so many driven innovators makes you feel like anything is possible. -New Courses and Exciting Challenges: With the first part of the semester over, I’m excited to dive into new courses. One standout is Innovation and Global Health Systems with Professor Rifat Atun. It’s an intensive, project-based class that challenges us to apply systems thinking and develop a healthcare venture within just eight weeks. The interactive format, coupled with insights from guest speakers across various sectors, makes this course extremely engaging. - Looking Forward to the SIIAM II Annual Meeting in Milan: I’ll be missing Thanksgiving in the US but for a good reason: I’ll be back in Milan for the SIIAM-Società Italiana Intelligenza Artificiale in Medicina II Annual Meeting on November the 30th. Over the past year, with the SIIAM Board we have worked tirelessly to organize this event, which is not just a scientific conference but a significant step toward building an AI ecosystem in Italy. More details here: https://lnkd.in/dHETd_SD

As #AI marches ahead in healthcare, some centers are investing significantly in their infrastructure and collaborations to support model development, application, and evaluation. Breaking down silos among clinical care, basic science, data science, IT, and healthcare data management is essential for the success of these centers. However, the approaches to achieving this vary widely. It will require significant financial investment: Mount Sinai Health System recently opened the Hamilton and Amabel James Center for Artificial Intelligence and Human Health, backed by a $100 million investment. This highlights the level of commitment needed to build robust AI ecosystems (https://lnkd.in/ghH_y-XC). It will require forward thinking: Washington University School of Medicine in St. Louis and BJC Health System have launched the joint Center for Health AI (https://lnkd.in/gXFwiGFt) incorporating opportunities for medical residents and students to gain skills in AI-driven care delivery. Integrating AI education into medical training is a key step forward. It requires collaboration across disciplines: The Department of Biomedical Informatics (DBMI) at Vanderbilt University Medical Center has launched its center for health Artificial Intelligence (AI) – ADVANCE (AI Discovery and Vigilance to Accelerate Innovation and Clinical Excellence). This center, Co-directed by Peter Embí, M.D., M.S. and Brad Malin (https://lnkd.in/gja4fcra) emphasizes the need to break down silos among clinical care, basic science, and data science. Centers like these set a standard for interdisciplinary teamwork. It may require collaboration between large healthcare systems and academic/scientific institutions with significant resources: Hartford HealthCare has launched The Center for AI Innovation in Healthcare and was created through collaboration with University of Oxford and Massachusetts Institute of Technology (https://lnkd.in/gZRGgRSi). Bringing together such institutions with significant technological resources and healthcare systems may be an effective model-- leveraging economies of scale (in this case technology know how and clinical care know how). The Google and Mayo Clinic partnership to advance generative AI applications in healthcare represents another promising model.(https://lnkd.in/gD4gfmcu). It will be fascinating to see which of these models thrives, the lessons learned, and how they shape the future of AI in healthcare. What do you think will drive the most successful outcomes? #UsingWhatWeHaveBetter

As #AI marches ahead in healthcare, some centers are investing significantly in their infrastructure and collaborations to support model development, application, and evaluation. Breaking down silos among clinical care, basic science, data science, IT, and healthcare data management is essential for the success of these centers. However, the approaches to achieving this vary widely. It will require significant financial investment: Mount Sinai Health System recently opened the Hamilton and Amabel James Center for Artificial Intelligence and Human Health, backed by a $100 million investment. This highlights the level of commitment needed to build robust AI ecosystems (https://lnkd.in/ghH_y-XC). It will require forward thinking: Washington University School of Medicine in St. Louis and BJC Health System have launched the joint Center for Health AI (https://lnkd.in/gXFwiGFt) incorporating opportunities for medical residents and students to gain skills in AI-driven care delivery. Integrating AI education into medical training is a key step forward. It requires collaboration across disciplines: The Department of Biomedical Informatics (DBMI) at Vanderbilt University Medical Center has launched its center for health Artificial Intelligence (AI) – ADVANCE (AI Discovery and Vigilance to Accelerate Innovation and Clinical Excellence). This center, Co-directed by Peter Embí, M.D., M.S. and Brad Malin (https://lnkd.in/gja4fcra) emphasizes the need to break down silos among clinical care, basic science, and data science. Centers like these set a standard for interdisciplinary teamwork. It may require collaboration between large healthcare systems and academic/scientific institutions with significant resources: Hartford HealthCare has launched The Center for AI Innovation in Healthcare and was created through collaboration with University of Oxford and Massachusetts Institute of Technology (https://lnkd.in/gZRGgRSi). Bringing together such institutions with significant technological resources and healthcare systems may be an effective model-- leveraging economies of scale (in this case technology know how and clinical care know how). The Google and Mayo Clinic partnership to advance generative AI applications in healthcare represents another promising model.(https://lnkd.in/gD4gfmcu). It will be fascinating to see which of these models thrives, the lessons learned, and how they shape the future of AI in healthcare. What do you think will drive the most successful outcomes? #UsingWhatWeHaveBetter

As we begin 2025, we're taking a moment to reflect on where we began seven years ago and, more recently, on all the progress we made in 2024! This year-in-review message from AIMI Center Director Curtis Langlotz recaps our organization's evolution, plus 2024 highlights, including: - Expansion of our AI-ready clinical datasets - Launch of a pilot program for commercial dataset use - Research teams funded in collaboration with Stanford Institute for Human-Centered Artificial Intelligence (HAI) - Booming AI + Health meeting attendance, and more! Dr. Langlotz's message also discusses our current strategic planning effort, supported by the Dean's office at Stanford University School of Medicine. "We see this planning initiative as an opportunity to build an adaptive organization that continues to support the strengths of AI and health activities across campus," he explains Read the full letter here: https://lnkd.in/e2zEpCAw #StanfordAIMI #AIInMedicine #EthicalAI #AIResearch #ClinicalDatasets #StanfordMed

✨ New Collaboration ✨ We’re thrilled to announce our exciting collaboration with Dr Pauldy Otermans, a leading figure in AI technology and neuroscience. We've been invited to test Dr Otermans' innovative Otermans Institute AI (OIAI) platform, which features AI-powered digital teachers designed to revolutionise learning and development. During our discussions with Dr Otermans, we explored the potential applications of AI in the healthcare and pharmaceutical industries. So our role will involve providing insights to enhance OIAI's application within these sectors 👩⚕️ 👨⚕️ Dr. Pauldy Otermans, a neuroscientist and psychologist, is at the forefront of AI technology, co-developing the world's first AI-powered digital human teachers and Teddy AI, an AI-driven study buddy for young children. OIAI represents a ground-breaking leap in learning and development, offering AI-driven digital teachers accessible anytime, anywhere 💻 We’re excited to contribute to this innovative journey and can't wait to share our progress with you. 🤩 Stay tuned for updates! 👀 #AI #Healthcare #LearningAndDevelopment #Innovation

🔍🤖💡 Join us for an enlightening journey from AI to Advocacy with Dr. Suresh K. Bhavnani, Professor of Biomedical Informatics, University of Texas Medical Branch; University of Texas, Health Science Center in Houston The Tecnológico de Monterrey's Institute for the Future of Education invites you to dive into a keynote presentation by Dr. Suresh K. Bhavnani on “From Artificial Intelligence to Advocacy: My Educational Journey into Policy Translation”. Date & Time: April 26th at 12:00 pm MTY time Unlock the potential of AI in healthcare policy-making and explore how the AI-policy gap can be bridged for a significant impact on patient care. Dr. Bhavnani, an esteemed Professor of Biomedical Informatics, will share valuable insights into using interpretable AI to identify social determinants of health within the 'All of Us' dataset and its implications on healthcare policies in the US. Key Takeaways: Discover how interpretable AI methods can classify subtypes of social determinants of health. Gain insights from Dr. Bhavnani’s experience in translating AI research into actionable healthcare policies. Understand the AI method characteristics that facilitate effective policy translation. Learn about the next steps in Dr. Bhavnani's mission to merge the worlds of AI and policy-making. Dr. Bhavnani brings a wealth of knowledge, with a Ph.D. in Computational Design and Human-Computer Interaction from Carnegie Mellon University and numerous distinguished awards. His leadership at the DIVA Lab at UTMB has contributed to groundbreaking research supported by NIH, CDC, and PCORI. 🔗 Join the Zoom Meeting: https://lnkd.in/eRMu-3gT This session will be moderated by Dr. Rasikh Tariq, and is brought to you in collaboration with the Challenge-Based Research Project “Complex Thinking Education for All (CTE4A): A Digital Hub and School for Lifelong Learners”. Don’t miss this opportunity to bridge the gap between AI and policy-making for a better future in healthcare! #AI #HealthcarePolicy #BiomedicalInformatics #UTMB #VisualAnalytics #PolicyTranslation #PublicHealth #ArtificialIntelligence #EducationalJourney #TecdeMonterrey

On November 13, 2024, Dr. Pat Mongkolwat, PhD, Dean of the Faculty of Information and Communication Technology, Mahidol University (ICT Mahidol), represented the President of Mahidol University at the academic conference on Artificial Intelligence (AI) and healthcare systems titled “Dialogue on Digital Trust in AI for Healthcare.” He also participated in a panel discussion on the topic “Areas of Opportunity and Challenge,” alongside faculty members from various universities at the Digital Trust Center, Nanyang Technological University Singapore. The panelists included: Paul Watson, UK National Innovation Center for Data (NIC-D), Newcastle University, Republic of Singapore Angela Daly, Professor of Law & Technology, Leverhulme Research Center for Forensic Science, University of Dundee, United Kingdom @Wilson Goh, Assistant Professor of Biomedical Informatics, Lee Kong Chian School of Medicine, School of Biological Sciences, Chief Data Scientist, NTU Center of AI in Medicine, Republic of Singapore Qingsong Wei, Principal Scientist and Group Manager, Institute of High Performance Computing (A*STAR IHPC), Republic of Singapore The “Dialogue on Digital Trust in AI for Healthcare” conference was co-organized by Nanyang Technological University and Newcastle University, Republic of Singapore. It aimed to provide a platform for AI experts from various universities to exchange knowledge on the role of AI in healthcare, focusing on new innovations and the integration of AI with medical sciences. The conference also facilitated discussions on managing security, governance, regulation, and safety issues related to the use of AI in health data collection and applications. https://lnkd.in/gPyHEjcq

🎉 Exciting News! 🎉 Our review paper, "A Comprehensive Survey of Foundation Models in Medicine," has been accepted for publication in IEEE Reviews in Biomedical Engineering (Impact Factor=17.2)! This collaborative effort was made possible by the incredible contributions of my co-authors: Wasif Khan, Seowung Leem, Kyle B. See, Ph.D. Joshua K. Wong, Shaoting Zhang. Together, we explored the transformative potential of foundation models in medicine, from enhancing clinical decision-making to driving biomedical research. Our paper highlights both the opportunities and challenges of these models, including interpretability, fairness, and adaptation to domain-specific needs. You can read the preprint here: https://lnkd.in/eaFw4czt. A special thank you to Dr. Bin He, PhD, Editor of IEEE Reviews in Biomedical Engineering, for his invaluable support and encouragement throughout the review process. Let’s continue pushing the boundaries of AI in medicine and fostering innovation for equitable and impactful healthcare solutions! #AIinMedicine #FoundationModels #BiomedicalEngineering #Research #HealthcareInnovation

#ASTUTENESS Project: AI-Driven Tools in Healthcare 👏Yesterday we started the mid-term in-person meeting at #Kalmar, Sweden 🇸🇪, where researchers from Linnaeus University Universidad de Murcia Semmelweis University Nantes Université participated, combining #computerscience, #sociology, and #medical perspectives to create a comprehensive approach. 🏥 Currently, decision support tools in healthcare software offer general recommendations based on clinical guidelines, requiring doctors to interpret and adapt them to local conditions. 🤖Recent advancements in #AI, particularly in machine learning and big data analysis, demonstrate the potential to process vast amounts of information. 💡The project's goal is to evaluate the confidence in AI-driven Clinical Decision Support Systems by delivering analytical guidelines based on real-world use cases. The #ASTUTENESS project is a part of the EUniWell - European University for Well-Being Research Incubator, aiming to advance healthcare through innovative AI-driven solutions.