PROBLEM STATEMENT:
In today’s world of automation, the skills and knowledge of a person could be utilized at the best places possible by automating tasks wherever possible.
As a part of the HealthIsWealth hospital automation system, you have been contracted as a professional data scientist who will build a system that would predict and estimate whether the patient should be categorized as an incare patient or an outcare patient with the help of several data points about the patients, their conditions and lab tests.
The difference between an inpatient and outpatient care is how long a patient must remain in the facility where they have the procedure done.
Inpatient care requires overnight hospitalization. Patients must stay at the medical facility where their procedure was done (which is usually a hospital) for at least one night. During this time, they remain under the supervision of a nurse or doctor.
Patients receiving outpatient care do not need to spend a night in a hospital. They are free to leave the hospital once the procedure is over. In some exceptional cases, they need to wait while anesthesia wears off or to make sure there are not any complications. As long as there are not any serious complications, patients do not have to spend the night being supervised.
Results:
Having trained all 6 models,XGBoost and the SVM models produced the best prediction; i.e whether a patient should be categorized as an inpatient or an outpatient.
Hence, with further feature slection and engineering, it is possible to get a higher F1_score with XGBoost and SVM.