Web: http://arxiv.org/abs/2209.10043

Sept. 22, 2022, 1:11 a.m. | Michael S. Yao, Allison Chae, Matthew T. MacLean, Anurag Verma, Jeffrey Duda, James Gee, Drew A. Torigian, Daniel Rader, Charles Kahn, Walter R. Witsc

cs.LG updates on arXiv.org arxiv.org

Early diagnosis of Type 2 Diabetes Mellitus (T2DM) is crucial to enable
timely therapeutic interventions and lifestyle modifications. As medical
imaging data become more widely available for many patient populations, we
sought to investigate whether image-derived phenotypic data could be leveraged
in tabular learning classifier models to predict T2DM incidence without the use
of invasive blood lab measurements. We show that both neural network and
decision tree models that use image-derived phenotypes can predict patient T2DM
status with recall scores …

arxiv diabetes image prediction type

More from arxiv.org / cs.LG updates on arXiv.org

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Tech Business Data Analyst

@ Fivesky | Alpharetta, GA

Senior Applied Scientist

@ Amazon.com | London, England, GBR

AI Researcher (Junior/Mid-level)

@ Charles River Analytics Inc. | Cambridge, MA

Data Engineer - Machine Learning & AI

@ Calabrio | Minneapolis, Minnesota, United States