Association of American Medical Colleges (AAMC)’s Post

Minnesota Emerging Software Advisory (MESA) and Jim Moar have been excellent guides to our leadership throughout the growth process. Here is a great post on how they helped us on our path to success! #entrepreneurship #tech #ai #startup

I’m really happy to share that with the publication of this study, we, at The Medical Futurist Institute, have taken a huge step toward a dream of mine I’ve had for many years: to make medical futures studies a new scientific field! This scoping review, ‘𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐭𝐡𝐞 𝐍𝐞𝐞𝐝 𝐟𝐨𝐫 𝐌𝐞𝐝𝐢𝐜𝐚𝐥 𝐅𝐮𝐭𝐮𝐫𝐞𝐬 𝐒𝐭𝐮𝐝𝐢𝐞𝐬: 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐅𝐫𝐨𝐦 𝐚 𝐒𝐜𝐨𝐩𝐢𝐧𝐠 𝐑𝐞𝐯𝐢𝐞𝐰 𝐨𝐟 𝐇𝐞𝐚𝐥𝐭𝐡 𝐂𝐚𝐫𝐞 𝐅𝐨𝐫𝐞𝐬𝐢𝐠𝐡𝐭’, that we published in JMIR takes a journey into the existing literature on the application of futures methods in healthcare, and it reveals that these methods have been successfully used to develop national strategies, inform healthcare policies, prepare for global threats like pandemics, and explore advancements in specialized medical fields like personalized medicine. However, we also proved that despite its potential, futures methods have been underutilized in the medical community. There’s a significant gap: the lack of structured methodologies and principles for employing futures techniques in healthcare, that’s exactly why we need medical futures studies.  You can read the full scoping review at the link in the comments, and I’ll be back with more exciting news about this topic soon! We have a lot of work to do.

🔍 Explore the future of medical predictions with our Prognostic Meta-Analysis Series! 🌐📊 Delve into the art of synthesizing prognostic studies, unraveling insights into predictive modeling, and understanding the dynamics of meta-analytic approaches. 🧬 Join leading experts as they navigate the realm of prognostic research, sharing valuable knowledge and unveiling the latest advancements. Elevate your understanding of predictive analytics and be at the forefront of groundbreaking discoveries! 🚀💡 Join our Grade 1 series. The last date of registration is 15th February 2024. Grade 1 is *compulsory* for attending advanced grades. https://lnkd.in/d5835VN6 #PrognosticAnalysis #ResearchInnovation #FuturePredictions

Listen to the interview (8 min): the model's training data doesn't match the population to which it is later applied.

🚀 Excited to announce that our paper, "How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?", led by Tony Wang and supervised by Rossella Arcucci, has been accepted to the Advancements in Medical Foundation Models workshop at NeurIPS 2024, where we explore how varying prompt styles affect the robustness of MedVLP models across multiple medical tasks. (https://lnkd.in/eh3AE3XT) Our findings reveal that MedVLP models exhibit unstable performance across different prompt styles, with sensitivity to the interpretability of prompts, indicating a lack of robustness and challenges in comprehending complex medical concepts. This underscores the need for more resilient methodologies to handle diverse zero-shot prompts effectively.

With any great innovation and impact to society you need transformative R&D and importantly constructive and collaborative oversight with feedback mechanisms and loops across the wider project objectives, and or curriculum / cohorts to deliver real tangible outcomes in an effective manner. Currently this does not exist, R&D ecosystems are disconnected and siloed creating bottlenecks to innovation and productivity and that’s exactly the problem they have solved. #reasearch #innovation #universities

Dr Emily Postan is the next speaker in our hybrid seminar series, with her talk 'Uncanny Kinds' on Thursday 2 May from 4pm-5pm, hosted by BRAID policy fellow Dr John Zerilli. You can attend in person at Inspace or online - get your tickets now at the link below 👇 In the fields of healthcare and health research, there is particular interest using machine learning (ML) to generated novel or refined diagnostic, prognostic, risk, and treatment categories. This talk interrogates the nature of these categories and their implications for the people thus (re)categorised. It approaches these questions through the lens of the philosophical idea of ‘human kinds’. It asks to what extent health-related categories generated by ML might function as human kinds and, if so, whether they might differ, in ethically significant ways, from socially-originating kinds. In doing so, it suggests that our understanding of responsible ML categorisation practices need to look beyond technical capabilities and clinical utility to consider wider personal and social impacts. Emily Postan is a Chancellor’s Fellow in Bioethics at the University of Edinburgh Law School and a Deputy Director of the J Kenyon Mason Institute for Medicine Life Sciences and the Law. #BraidUK #DIwebinars #ResponsibleAI #HealthcareEthics #HealthTech #Bioethics #AIinHealthcare #HealthResearch #EthicalAI #MedicalAI #AI #policy #AIpolicy Design Informatics, University of Edinburgh Arts and Humanities Research Council (AHRC) Edinburgh College of Art University of Edinburgh Law School https://lnkd.in/eeiWZDvx

Exciting news! ➡ Since our inception, Latent Knowledge has received support and mentorship from various faculty, students, and key research leaders throughout Columbia University. Now, we’re thrilled to officially announce our partnership with the Global Alliance for Preventing Pandemics, the technical workforce development and international outreach organization within the Center for Infection and Immunity at Columbia University Mailman School of Public Health. With an overall vision of medical equity and health independence, the GAPP is dedicated to supporting public health professionals in low- and middle-income countries to prevent pandemics and operate effective healthcare delivery, even in urgent circumstances. Where does Latent Knowledge come in? Through leveraging of our product LitView and LK's Research Services, we will: ✅ Support GAPP with AI for literature search and knowledge management ✅ Help standardize research methods around the world ✅ Create and study training data, language models, and machine learning algorithms in practice Our collaboration’s benefits extend beyond the GAPP program alone. In line with our shared mission to equip researchers worldwide with the best research practices, we’ll also be deploying LitView to the GAPP’s partner organizations around the globe to standardize research methods and explore the implementation of AI-based systems, an effort whose outcomes would have a ripple effect through public health and beyond. Endless thanks to Dr. J. Kenneth Wickiser, James Reilly, Jack Collins, Maya Levin, MS MPH, and Caroline King #publichealth #ai #partnership #startupecosystem

🎉 Exciting News! 🎉 Our team is thrilled to announce that we have been awarded an SGD $100K seed grant 🌱 from the "Crazy Ideas Competition" at the NUS School of Computing! We’re beyond excited to launch ✨CheckUp✨, a project taking on one of today’s biggest challenges: Healthcare Misinformation. 🚀 Led by our group's postdoc @Jiaying Wu, CheckUp ✅☝️ aims to bridge the gap between scientific communication and public understanding by developing an automated framework that ensures trustworthy, engaging healthcare information on social media platforms. Through ✨CheckUp✨, we’re combining advanced predictive models and LLMs to help healthcare content reach wider audiences without compromising information accuracy. Stay tuned as we work towards safeguarding public health by making reliable scientific knowledge accessible and compelling! 🌏 💡 We're striving to combat the 29% of the world's population that, according to a recent study, has been exposed to healthcare misinformation. So, keep an eye out as we gear up to revolutionize the way we consume healthcare information. We're committed to bridging the gap between science and society, one post at a time! #ScienceCommunication #LLM #SocialMedia #NUSComputing

🚀 Excited to share our latest research published in the World Wide Web Journal! I will also give a lightning talk of this paper in the DSAI Summit 2024 of Faculty of IT, Monash University! We introduced OntoMedRec, a novel approach to medication recommendation using logically-pretrained and model-agnostic ontology encoders. OntoMedRec addresses the data sparsity problem in electronic health records (EHRs) by leveraging medical ontologies. Our framework uniquely utilizes an explainable logic tensor network to effectively model the hierarchical relationships in medical ontologies. This enhances the interpretability and accuracy of medication recommendations. 🌟 Key Highlights: Model-agnostic integration: Enhances various downstream medication recommendation models. Comprehensive experiments: Proven improvements in both normal and few-shot scenarios. Open Source: Check out the GitHub repository within the paper! 🔗 Read the full paper here : https://lnkd.in/gMc_9_iU #healthinformatics #medicationrecommendation #AIinHealthcare