/Diabetes-Treatment-analysiss

Diabetes is a medical condition that affects approximately 1 in 10 patients in the United States. According to Ostling et al, patients with diabetes have almost double the chance of being hospitalized than the general population (Ostling et al 2017). Therefore, we would be creating a model, which will focus on: 1.The hospitals are evaluating efficiency of Insulin based treatment for patients, recommend if solo insulin treatments work well towards the above stated objective. We would be focusing on the result of insulin on different age groups 2. For a new patient, given his medical history and characteristics, should we recommend solo insulin or a conjunction of other drugs/ treatment?

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Diabetes-Treatment-analysiss Diabetes is a medical condition that affects approximately 1 in 10 patients in the United States. According to Ostling et al, patients with diabetes have almost double the chance of being hospitalized than the general population (Ostling et al 2017). Therefore, we would be creating a model, which will focus on: 1.The hospitals are evaluating efficiency of Insulin based treatment for patients, recommend if solo insulin treatments work well towards the above stated objective. We would be focusing on the result of insulin on different age groups
2. For a new patient, given his medical history and characteristics, should we recommend solo insulin or a conjunction of other drugs/ treatment?

Knowing the data

The data are submitted on behalf of the Center for Clinical and Translational Research, Virginia Commonwealth University, a recipient of NIH CTSA grant UL1 TR00058 and a recipient of the CERNER data. John Clore (jclore '@' vcu.edu), Krzysztof J. Cios (kcios '@' vcu.edu), Jon DeShazo (jpdeshazo '@' vcu.edu), and Beata Strack (strackb '@' vcu.edu). This data is a de-identified abstract of the Health Facts database (Cerner Corporation, Kansas City, MO). Citation: Beata Strack, Jonathan P. DeShazo, Chris Gennings, Juan L. Olmo, Sebastian Ventura, Krzysztof J. Cios, and John N. Clore, “Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records,” BioMed Research International, vol. 2014, Article ID 781670, 11 pages, 2014. The dataset has over 50 features including patient characteristics, conditions, tests and 23 medications. Some key features of the Data Set:

  1. Numerical Features: 1 Time in Hospital 2 # of lab procedure 3 # of medications 4 # of outpatient visits 5 # of emergency visit 6 # of admissions

  2. Categorical Features: 1 Medication change 2 HbA1c test 3 Race 4 Gender 5 Age 6 Readmission