Data
Diabetes130US

Diabetes130US

active ARFF Publicly available Visibility: public Uploaded 03-01-2023 by Leo Grin
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Dataset used in the tabular data benchmark https://github.com/LeoGrin/tabular-benchmark, transformed in the same way. This dataset belongs to the "classification on numerical features" benchmark. Original link: https://openml.org/d/4541 Original description: Author: Attila Reiss, Department Augmented Vision, DFKI, Germany, "attila.reiss '@' dfki.de Date: August 2012. Source: UCI Please cite: 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. This data has been prepared to analyze factors related to readmission as well as other outcomes pertaining to patients with diabetes. Source 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). Data Set Information The dataset represents 10 years (1999-2008) of clinical care at 130 US hospitals and integrated delivery networks. It includes over 50 features representing patient and hospital outcomes. Information was extracted from the database for encounters that satisfied the following criteria: (1) It is an inpatient encounter (a hospital admission). (2) It is a diabetic encounter, that is, one during which any kind of diabetes was entered to the system as a diagnosis. (3) The length of stay was at least 1 day and at most 14 days. (4) Laboratory tests were performed during the encounter. (5) Medications were administered during the encounter. The data contains such attributes as patient number, race, gender, age, admission type, time in hospital, medical specialty of admitting physician, number of lab test performed, HbA1c test result, diagnosis, number of medication, diabetic medications, number of outpatient, inpatient, and emergency visits in the year before the hospitalization, etc. Attribute Information Detailed description of all the attributes is provided in Table 1 of the paper. Relevant Papers 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. [Web Link](https://www.hindawi.com/journals/bmri/2014/781670/)

8 features

readmitted (target)nominal2 unique values
0 missing
time_in_hospitalnumeric14 unique values
0 missing
num_lab_proceduresnumeric116 unique values
0 missing
num_medicationsnumeric71 unique values
0 missing
number_outpatientnumeric38 unique values
0 missing
number_emergencynumeric31 unique values
0 missing
number_inpatientnumeric18 unique values
0 missing
number_diagnosesnumeric16 unique values
0 missing

19 properties

71090
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
7
Number of numeric attributes.
1
Number of nominal attributes.
12.5
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
1
Average class difference between consecutive instances.
87.5
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
12.5
Percentage of nominal attributes.
50
Percentage of instances belonging to the most frequent class.
35545
Number of instances belonging to the most frequent class.
50
Percentage of instances belonging to the least frequent class.
35545
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

2 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: readmitted
0 runs - estimation_procedure: 4-fold Crossvalidation - target_feature: readmitted
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