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Patient satisfaction survey.
Data courtesy of http://www.hcahpsonline.org. Centers for Medicare & Medicaid Services, Baltimore, MD.
Stroke prediction based on a random sample of the approximately 6 million patient records from GE Medical Quality Improvement Consortium (MQIC) database.
In the U.K 2.6 million people have diabetes.It can have serious health consequences if not diagnosed immediately. A new improved way of detecting Diabetes which can change lives with this model. Data UCI
Model predicting hospital readmissions, by Major Diagnostic Category (MDC) and age.
Data sourced from HCUPnet - a services of the US Department of Health & Human Services: http://hcupnet.ahrq.gov/HCUPnet.jsp.
Model that predicts which percentage of patients will rate a hospital at 9 or 10, based on a dataset of hospital patient surveys. It shows which survey items and which scores are important for a good overall result. The data is from a list of hospital ratings for the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). HCAHPS is a national, standardized survey of hospital patients about their experiences during a recent inpatient hospital stay. https://data.medicare.gov/dataset/Survey-of-Patients-Hospital-Experiences-HCAHPS-/rj76-22dk
The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups:
- Class 01 refers to 'normal' ECG
- Classes 02 to 15 refers to different classes of arrhythmia
- Class 16 refers to the rest of unclassified ones.
For the time being, there exists a computer program that makes such a classification. However there are differences between the cardiolog's and the programs classification. Taking the cardiolog's as a gold standard we aim to minimise this difference by means of machine learning tools.
Car accidents in UK during 2012.