Upcoming Webinar: Thursday, June 8, 2023, 3:00-4:00 p.m. ET/12:00-1:00 p.m. PT
Title: Making AI Trustworthy and Referenceable for Clinical Applications – A Commercial Use-case
Healthcare is anchored in evidence and explainability. But today the dissemination, use and feedback of this evidence is predominately document based. In this form, it adds to clinician workload, errors, biases, and waste, significantly impacting patients and all stakeholders in the system. As advanced AI evolves (e.g. as shown by GPT4), there is also a potential for negative impact on medicine, as such AI may not be rooted in evidence or be traceable to high-quality references. Some AI may add further cognitive burden on physicians to assess the trustworthiness of response.
To solve these problems, the presenting company, RecoverX, provides the referenceable, evidence anchor for AI. They are building “Referenceable AI” technology to:
- Enable AI that is trustworthy, controllable and referenceable, across the system
- Disseminate and strengthen evidence based medicine knowledge and guidelines
- Enable the medical profession to be in control of AI, not have AI get out of control
RecoverX’s products include:
- Clinical Copilot: providing real-time, contextualized, and referenceable insights on potential diagnosis, treatments and next-best-actions for clinician consideration in workflow. Clinical Copilot also enables Generative AI, such as GPT and Claude, to be directed to utilize validated and referenced AI in a controllable, referenceable manner.
- Computational Evidence Platform: enabling evidence based content and guidelines to be made AI-enabled and referenceable for multiple use cases.
RecoverX is a healthcare AI and computational evidence company backed by Health2047, the American Medical Association’s ventures and innovation arm. Their mission is to help scale equitable, science-based care.
Webinar Agenda:
- Introduction to RecoverX
- Overview of AI and Generative AI
- Barriers to making AI trustworthy and referenceable
- Demo of Clinical Copilot
- Discussion on opportunities and challenges of AI from a physician perspective
The webinar will be recorded and posted to this page afterwards. Please note that this webinar is not accredited for CME credit.
Panelist Bios:
Jennifer May Lee, MD is the Chief Medical Officer at RecoverX. She completed her residency and fellowship training at Columbia University Medical Center and worked at NYU Langone and Bellevue Hospital on the Chest service and WTC survivors program. Her focus at RecoverX is on building computational data that can be used for AI healthcare delivery and designing a healthcare platform to simplify and enhance the physician and patient experience.
Carl Bate is the founder and CEO of RecoverX. Carl is an engineer and entrepreneur with a computer science background. RecoverX has been founded to help scale equitable, science-based healthcare, as a response to the rising complexities of and opportunities for medicine, through combining the best of expert, evidence and AI. Prior to RecoverX, Carl led the AI group at Arthur D. Little and was CTO at Capgemini. A coder since aged 11, Carl lives in San Francisco, is a Fellow of the British Computer Society, and the prior Chair of its Futures Group where he focused on Web Science initiatives.
David Epstein is the Chief Product Officer at RecoverX where he focuses on product design, development, and client relations. Previously he was the CEO of medCPU, a leader in real-time, natural language processing-based clinical decision support and analytics tools. He has over 40 years of technical and executive leadership experience in companies ranging from startups to Fortune 100s including BBN Labs, IBM’s Research Division and Software Group, Allscripts and Deloitte Consulting’s Life Sciences and Healthcare Practice. A computer scientist by training, David is the holder of 15 US patents, author of 16 peer-reviewed technical articles, and the recipient of 11 major IBM awards for outstanding contributions and technical excellence. He holds BA and MS degrees from Harvard, completed PhD work through qualifiers at NYU/Courant, and received an MBA from Columbia.