Difference between revisions of "SOCR AmStat SII 2023"
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=== Data Science and Predictive Analytics (DSPA2)=== | === Data Science and Predictive Analytics (DSPA2)=== | ||
| − | [[Image:Data_Science_and_Predictive_Analytics_2ed(book_cover).png|100px|thumbnail|right| [https:// | + | [[Image:Data_Science_and_Predictive_Analytics_2ed(book_cover).png|100px|thumbnail|right| [https://dspa2.predictive.space/ DSPA2] ]] |
* Speaker: [https://www.socr.umich.edu/people/dinov/ Ivo Dinov] | * Speaker: [https://www.socr.umich.edu/people/dinov/ Ivo Dinov] | ||
Revision as of 08:47, 3 March 2023
Contents
SOCR News & Events: 2023 AmStat SII Section Seminar Data Science and Predictive Analytics (DSPA2)
Overview
This monthly webinar is part of the ongoing Statistics in Imaging (SII) section of the American Statistical Association (AmStat).
Organizers
- Julia Fisher, BIO5 Institute, University of Arizona.
- Dan Spencer, Indiana University Bloomington.
Session Logistics
- Date/Time: March 14, 2023, 1 PM PT (4PM ET, GMT-5).
- Zoom Link.
- AmStat SII Community website (AmStat login required).
Presentations
Data Science and Predictive Analytics (DSPA2)
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- Speaker: Ivo Dinov
- Title: A brief overview of the revised Data Science and Predictive Analytics: Biomedical and Health Applications using R book
- Book URL
- Outline Summary
- Supporting Book Website.
Denoising Diffusion Models in Medical Imaging
- Speaker: Ali Bilgin
- Title: Denoising Diffusion Models in Medical Imaging
- Abstract: Over the past decade, generative modeling using neural networks has received significant attention. Denoising diffusion models are the latest generation of generative models and over the last two years, they have been used in various image processing applications. In this talk, I will provide an introduction to these models and discuss their use in some medical imaging applications.
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