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DTSTAMP:20260504T231259Z
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DTSTART;TZID=America/Chicago:20260413T180000
DTEND;TZID=America/Chicago:20260413T184500
DESCRIPTION:Join us for the first webinar in the EMBS Twin Cities Engineeri
 ng in Medicine series\, sponsored by the IEEE Engineering in Medicine and 
 Biology Society – Twin Cities Chapter.\n\nThis session will explore how 
 generative AI tools—such as large language models and image generators
 —are beginning to reshape clinical care\, research\, and global health m
 easurement. We will discuss how Denoising Diffusion Probabilistic Models (
 DDPM) can reduce radiation dose in breast imaging while preserving diagnos
 tic quality\, how synthetic data can help address bias and gaps in real‑
 world healthcare datasets\, and how GenAI is being deployed to summarize m
 edical visits and navigate complex electronic health records. The webinar 
 will close with an open\, interactive discussion on where these tools “h
 appily cross ethical boundaries\,” examining unresolved questions around
  safety\, transparency\, consent\, and equity in and beyond healthcare.\n\
 nCo-sponsored by: Jamie Hamilton - from Southeastern Michigan EMBS chapter
 \n\nSpeaker(s): Fred Nugen\, \n\nAgenda: \n1 hour of a virtual talk follow
 ed by questions.\n\nVirtual: https://events.vtools.ieee.org/m/548861
LOCATION:Virtual: https://events.vtools.ieee.org/m/548861
ORGANIZER:riaghosh19@gmail.com
SEQUENCE:54
SUMMARY:EMBS Webinar series: Three uses of Generative AI in Medicine: reduc
 ing radiation\, measuring global burden of disease\, and happily crossing 
 ethical boundaries
URL;VALUE=URI:https://events.vtools.ieee.org/m/548861
X-ALT-DESC:Description: <br /><p>Join us for the first webinar in the EMBS 
 Twin Cities Engineering in Medicine series\, sponsored by the IEEE Enginee
 ring in Medicine and Biology Society &ndash\; Twin Cities Chapter.</p>\n<p
 >This session will explore how generative AI tools&mdash\;such as large la
 nguage models and image generators&mdash\;are beginning to reshape clinica
 l care\, research\, and global health measurement. We will discuss how Den
 oising Diffusion Probabilistic Models (DDPM) can reduce radiation dose in 
 breast imaging while preserving diagnostic quality\, how synthetic data ca
 n help address bias and gaps in real‑world healthcare datasets\, and how
  GenAI is being deployed to summarize medical visits and navigate complex 
 electronic health records. The webinar will close with an open\, interacti
 ve discussion on where these tools &ldquo\;happily cross ethical boundarie
 s\,&rdquo\; examining unresolved questions around safety\, transparency\, 
 consent\, and equity in and beyond healthcare.</p>\n<p><img src="https://e
 vents.vtools.ieee.org/vtools_ui/media/display/5d3518dd-1140-410e-b617-2c15
 5c8c3b20"></p><br /><br />Agenda: <br /><p>1 hour of a virtual talk follow
 ed by questions.</p>
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