Introducing the Stanford Healthcare Innovation Community (SHIC) and Its New Leadership We're thrilled to announce the launch of the Stanford Healthcare Innovation Community (SHIC) and introduce our dynamic leadership team! SHIC is a cross-disciplinary club uniting emerging healthcare leaders passionate about solving the most challenging problems in healthcare. We bring together Stanford students from diverse backgrounds, including researchers, medical professionals, financiers, technologists, entrepreneurs, and policy-makers. Meet Our Co-Presidents: ? Riley Nisbet- Industry & Alumni Engagement ? Sonia Sarda - Multidisciplinary Engagement ? Rich Bailey, MS - Brand, Funding, Mentorship Our co-presidents share their vision for SHIC: "Riley is energized to see the healthcare-driven community at Stanford come together to learn and build together!" "Sonia is excited to create a community where members can meet others passionate about healthcare, and put together different skillsets to create an impact in the space." "Rich is passionate about creating a vibrant, inclusive community that extends beyond Stanford affiliations and welcomes students from all levels of study, while offering mentorship opportunities in the rapidly evolving healthcare industry." Why SHIC? The US healthcare system is complex, often leading to misaligned incentives. To make a positive impact toward the Quintuple Aim, we need innovations from teams that understand the entire cross-functional healthcare landscape. Benefits of Joining SHIC: ? Multidisciplinary networking opportunities ? Engaging discussions with healthcare thought leaders ? Access to a lifelong healthcare alumni network SHIC is more than just a club – it's a gateway to shaping the future of healthcare. While starting with the Stanford graduate community, we aspire to extend our reach beyond campus walls. Join us in building a community that will drive meaningful change in healthcare. Whether you're a researcher, clinician, entrepreneur, or policy enthusiast, SHIC has a place for you. To learn more, visit our LinkedIn page: https://lnkd.in/gbmebW8q For more information or to get involved, please contact one of our co-presidents (tagged in this post). Together, we can bridge disciplines, foster innovation, and work towards a better healthcare system for all. #HealthcareInnovation #StanfordMedicine #MultidisciplinaryCollaboration #StanfordHealthcareInnovationCommunity #SHIC
Stanford Healthcare Innovation Community
医院和医疗保健
We are graduate students and alumni with a passion for improving healthcare through innovative collaboration.
关于我们
SHIC is a cross-discipline community of emerging healthcare leaders that are united by a passion for solving healthcare’s most challenging problems. SHIC is a club sponsored by Stanford and consists of Stanford graduate students including researchers, medical professionals, financiers, technologists, entrepreneurs and policy-makers. SHIC provides programming that allows these multi-disciplinary emerging leaders to form strong bonds and learn from thought-leaders.
- 所属行业
- 医院和医疗保健
- 规模
- 201-500 人
- 类型
- 非营利机构
- 创立
- 2020
动态
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Stanford Healthcare Innovation Community转发了
Fantastic summary by Jan Beger about our recent Nature Medicine manuscript on clinical text summarization led by Dave Van Veen.
This study demonstrates that adapted large language models can outperform medical experts in clinical text summarization tasks, including radiology reports, patient questions, progress notes, and doctor-patient dialogues. The effectiveness of LLMs was evaluated through a combination of quantitative assessments and a clinical reader study involving 10 physicians. The findings suggest potential for integrating LLMs into clinical workflows to reduce documentation burden and improve patient care. 1?? Adapted LLMs outperform medical experts in summarizing clinical texts, with higher scores for completeness, correctness, and conciseness. 2?? Quantitative and qualitative evaluations across multiple clinical summarization tasks reveal LLMs' superiority. 3?? In the clinical reader study, adapted LLM summaries were preferred over medical expert summaries in 36% of cases, with another 45% deemed equivalent, showing a high acceptance among physicians. 4?? Safety analysis indicated that LLM summaries had a lower likelihood and extent of potential medical harm compared to those created by medical experts. 5?? Fabricated information was less frequent in LLM summaries than in those by medical experts, showcasing the model's higher accuracy in information representation. 6?? A nuanced categorization of fabricated information revealed LLMs are more reliable in avoiding misinterpretations, factual inaccuracies, and hallucinations. 7?? Clinical integration of LLMs could reduce documentation burden, allowing clinicians to focus more on patient care. The paper illustrates the potential of LLMs in healthcare, emphasizing their ability to alleviate the documentation workload on clinicians while maintaining or improving the quality of clinical summaries. ??? Dave Van Veen, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek, Ma?gorzata Po?acin, Eduardo Pontes Reis, Anna Seehofnerová, Nidhi Rohatgi, Poonam Hosamani, Dr. William Collins, Neera Ahuja, Curtis Langlotz, Jason Hom, Sergio Gatidis, John Pauly, Akshay Chaudharil. Nature Medicine. Publication date: 2024. DOI: 10.1038/s41591-024-02855-5 (Behind paywall) ? Subscribe to my newsletter and stay at the forefront of groundbreaking studies. Get started here: https://lnkd.in/eR7qichj.
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Stanford Healthcare Innovation Community转发了
VP, Digital Transformation and Head, Alliances at Intelliswift | A Digital Trailblazer Driving Business Transformation with AI and Automation | HIMSS Northern CA Chapter | Follow me on X @sanjaykalra
What is real and what is illusion with #healthcare #AI? In a preview of his upcoming #HIMSS24 session, Dr. Jonathan H. Chen, assistant professor at the Stanford Center for Biomedical Informatics Research, offers perspective on discerning what's real in AI, what's hype and what it all means for patient care. https://lnkd.in/gEHBV4FF
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Stanford Healthcare Innovation Community转发了
Great work by the entire Stanford Institute for Human-Centered Artificial Intelligence (HAI), Cerebral, Jonathan H. Chen, Olivier Gevaert, Akshay Swaminathan, and Ivan Lopez to put together a CMD-1 (Crisis Message Detector 1) model that can be used in #behavioralhealth #augmentedintelligence workflows - surfacing messages for #clinical #therapists to review and act in a #mentalhealth crisis.
Using NLP to Detect Mental Health Crises
hai.stanford.edu