Prediction-of-Shows-and-No-Shows-in-HealthCare-Industry

Healthcare has become one of India’s largest sector, both in terms of revenue and employment. Healthcare comprises hospitals, medical devices, clinical trials, outsourcing, telemedicine, medical tourism, health insurance and medical equipment.
No shows has become common in healthcare industry where customer books the date but don't appear on the booking date. In order to keep this in mind, ML model in created where prediction is done whether the customer will appear on that day or not using various ML models.
The data includes the wheather report of days of booking based on per hour. The booking schedule that describes the total bookings that have taken place and transaction report that includes the charged amount that has been done for customers who have shown up for the specific days.
At the end, the percentage of no shows has been included as the result.

Libraries Used:

Pandas, Numpy, Matplotlib, Seaborn, Plotly

Programing Language

Python

IDE Used

Jupyter Notebook

Algorthms Used

Label Encoder, One Hot encoder, Power Transformer, Randomised Search CV, Linear regressor, Decision Tree, Random Forests, XG Boost