Monitoring ICU data is becoming an important task as , detecting and tracking the change in data pattern and prediction of change in state of the patient in the near future. By this we not only meticulously monitor patients but also can keep track of changes in patients' physical state. We also have to analyse past values and predict the future values and state through a VAR model.
The MIMIC Database (https://physionet.org/content/mimicdb/1.0.0/) includes data recorded from over 90 ICU patients. The data in each case include signals and periodic measurements obtained from a bedside monitor as well as clinical data obtained from the patient's medical record. The recordings vary in length; almost all of them are at least 20 hours, and many are 40 hours or more. In all, the database contains nearly 200 patient-days of real-time signals and accompanying data.
the main application is app.py run app.py and you should have an application that can run python application as app.py is written using flask so to run that you will be given a link, copy that http link and paste on your browser and run