Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Medicine and Health Sciences

South Dakota State University

2019

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

South Dakota State University : Research Fall 2019, South Dakota State University Oct 2019

South Dakota State University : Research Fall 2019, South Dakota State University

Research: South Dakota State University

[Page] 2 Curcumin formulation on its way to health product market
[Page] 4 Flexibility key to forging research partnership with Kodo Kids
[Page] 6 Researcher examines hope among children in Flint, Michigan
[Page] 7 Plant pathologist battles stem canker
[Page] 8 Removing ‘Typhoid Marys’ restores health of Custer bighorn sheep herd
[Page] 10 Breeder, food scientist help improve quality of oats, increase local production
[Page] 13 SDSU, community leaders explore new ways to drive research, partnerships
[Page] 14 SDSU, community leaders explore new ways to drive research, partnerships
[Page] 16 Engineering builds business connections through Research Park
[Page] 17 Research …


Predicting Unplanned Medical Visits Among Patients With Diabetes Using Machine Learning, Arielle Selya, Eric L. Johnson Feb 2019

Predicting Unplanned Medical Visits Among Patients With Diabetes Using Machine Learning, Arielle Selya, Eric L. Johnson

SDSU Data Science Symposium

Diabetes poses a variety of medical complications to patients, resulting in a high rate of unplanned medical visits, which are costly to patients and healthcare providers alike. However, unplanned medical visits by their nature are very difficult to predict. The current project draws upon electronic health records (EMR’s) of adult patients with diabetes who received care at Sanford Health between 2014 and 2017. Various machine learning methods were used to predict which patients have had an unplanned medical visit based on a variety of EMR variables (age, BMI, blood pressure, # of prescriptions, # of diagnoses on problem list, A1C, …