...
Data Transparency Winter Event 2025 |
Active since 2014, PHUSE’s Data Transparency Working Group has provided subject matter expertise for the review of draft deliverables and guidance documents from regulatory bodies (such as the EMA and Health Canada), as well as other industry organisations (such as TransCelerate) and academia. Since their inception in 2020, the free-to-attend Data Transparency Events have gone from strength to strength. These virtual events have created an unrestricted space where questions can be asked and challenges addressed. Individuals passionate about the area can come together to share vital knowledge, develop new ideas and spark innovation through presentations, panel discussions and Q&A sessions alongside experts in the data-sharing field. The PHUSE Data Transparency Autumn Event took place on 4–6 February 2025. Data Transparency Events offer you the chance to gain knowledge and experience from a wide data transparency community, allowing you to come together with experts from a variety of companies and backgrounds. During this virtual event, presentations were delivered across the three days in bitesize chunks from 15:00-17:30 (GMT). There was also a panel discussion and Q&A session focused on the day's themes. Links to the event presentations and daily recordings can be found /wiki/spaces/WEL/pages/91979777. |
Responsible AI in a Healthcare System
Responsible AI in a Healthcare System
As the use of artificial intelligence (AI) moves from being a curiosity to a necessity, it is clear that the benefit obtained from using AI models to prioritise care interventions is an interplay of the model’s performance, the capacity to intervene, and the benefit/harm profile of the intervention. After a brief review of the kinds of use cases that AI can serve across multiple medical specialties, we will discuss Stanford Healthcare’s efforts to shape the adoption of health AI tools to be useful, reliable and fair so that they lead to cost-effective solutions that meet healthcare’s needs.
We will conclude with the rationale and vision for collaborative activities such as the Coalition for Health AI. We will discuss how the adoption of LLMs in medicine needs to be shaped by performing the evaluations that specify the desired benefits and verify those benefits via testing in real-world deployments. The conversation will draw on examples from multiple specialties including pathology, cardiology, internal medicine, surgery, psychiatry and oncology.
In this forum we will be joined by Dr Nigam Shah!
Dr Nigam Shah has been Chief Data Scientist at Stanford Healthcare since 2022. He leads artificial intelligence and data science efforts for advancing the scientific understanding of disease, improving the practice of clinical medicine and orchestrating the delivery of healthcare. His research group analyses multiple types of health data (EHR, claims, wearables, weblogs and patient blogs) to answer clinical questions, generate insights and build predictive models for the learning health system.
This Community Forum will be taking place virtually on 18 February at 16:00-17:30 (GMT) / 11:00-12:30 (EST) / 17:00-18:30 (CET)
| Info |
|---|
End-to-End RBQM Education – Make the Most Out of Innovation and Ensure it’s Done Right! | ||
|---|---|---|
Join the webinar to learn why change is not only an idea but a necessity. We will explore where old habits need to be retired and where new initiatives have proven to increase efficiency and reduce cost without impacting on quality. This Webinar will be taking place virtually on 20 February at 15:00-14:00 (GMT) / 8:00-9:00 (EST) / 14:00-15:00 (CET)
|
...