Predicting patient death
About project
Bisiness effect
The model made it possible to predict the likelihood of death of patients and separate severe cases from the lungs.
Solution
Development of a model that predicts the likelihood of patient death. For analysis, data from biological analyzes of the patient and various socio-demographic indicators are received.
A task
It is necessary to predict the mortality of patients in a medical clinic within a given period of time and in general.
Stages of development
Тechnology
XGBoost acts as a machine learning algorithm. The model prediction add-on, xgbse, was also used.
Model implementation
4.
Building a model
3.
Creating a Showcase
2.
External data collection
1.
Project team
Developer
Frank Sh.
Areas of use
This technology has applications in medical clinics. Based on the results of the model, doctors are given a recommendation system for predicting the death of a patient.
