Context:
Our healthcare client was conducting a clinical trial where the hospital adopted a Python powered system to build a predictive model that identifies high risk patients so interventions can be planned.

Resolution:
To solve this, a simple AI tool was developed by our specialized team, creating outputs on patient risk scores and feature importance rankings, along with an ROC curve, confusion matrix, and automated dashboards in Jupyter Notebook or exported to PDF.

Result:
This improved diagnosis accuracy, identified patients at high risk of readmission, reduced costs, improved patient outcomes, and demonstrated compliance with healthcare quality standards.