[Eoas-seminar] [Seminar-announce] Scientific Computing Colloquium with Zhe He

[eoas-seminar at lists.fsu.edu]

"Towards An AI-Powered Application for Laboratory Test Results Comprehension "

Zhe He
Interim Director for the Institute for Successful Longevity
Associate Professor in the School of Information (iSchool)
Florida State University

Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic. All are welcome to attend.

NOTE: In-person attendance is requested. Zoom access is intended for external (non-departmental) participants only.

https://fsu.zoom.us/j/94273595552
Meeting # 942 7359 5552

🎦 Colloquium recordings will be made available here, https://www.sc.fsu.edu/colloquium<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fcolloquium&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7C686bd5facd894e8fae4208dce0a86b4a%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C638632261159113839%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=4vnOEzTjRg7gqxYqf5xW%2F06bziuVQYGrSjThMfFvugE%3D&reserved=0>

Wednesday, Oct 2, 2024, Schedule:

* 3:00 to 3:30 PM Eastern Time (US and Canada)
☕ Nespresso & Teatime - 417 DSL Commons

* 3:30 to 4:30 PM Eastern Time (US and Canada)
🕟 Colloquium - 499 DSL Seminar Room


Abstract:

Viewing laboratory test results is the most frequent activity for patients accessing patient portals, yet the interpretation of these results can be challenging and confusing. While previous research has explored various methods of presenting lab results, there has been limited focus on providing tailored information support based on an individual's medical context. Our AHRQ-funded LabGenie project addresses this gap by developing a user-centered, web-based tool designed to enhance patient engagement and understanding of lab results, particularly for older adults with multiple chronic conditions who often face difficulties due to limited health literacy and technology skills. In this talk, I will present a series of studies that investigate the challenges older adults face in understanding lab test results and our efforts to leverage generative AI and advanced biostatistical methods to provide better support. Our formative research included a survey of 270 patients to identify factors affecting their comprehension of lab results. Additionally, we evaluated the effectiveness of four large language models (LLMs) for answering lab-related questions sourced from a community Q&A website. To further enhance the accuracy of lab test interpretation, we analyzed the seasonality of lab results in a cohort of older adults with Alzheimer’s disease. We also used knowledge-augmented LLMs to determine normal ranges of various condition, predict differential diagnoses based on lab results and other medical information, and generate tailored questions for patients to follow with their doctors.

Through these studies, we aim to develop innovative, AI-driven approaches that improve the accessibility and comprehension of lab results for older adults, ultimately promoting better patient engagement and shared decision-making in healthcare.


Additional colloquium details can be found here,
https://www.sc.fsu.edu/news-and-events/colloquium/1818-colloquium-with-zhe-he-2024-10-02<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fcolloquium%2F1818-colloquium-with-zhe-he-2024-10-02&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7C686bd5facd894e8fae4208dce0a86b4a%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C638632261159113839%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=0IiuijN4mRwaQYs4Fb4i1E2Onxo73pSve5DiZIpGL1I%3D&reserved=0>
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