"Enhancing Clinical Outcomes"

Projects Overview

Developed predictive analytics using machine learning to identify patients at high risk of readmission.

Enabled hospitals to design targeted intervention programs for high-risk patients.

Utilized Scikit-learn and Google Cloud AI to ensure scalable and accurate predictions.

Our Process

Step 01

Data Collection

Aggregated patient data from multiple sources, including EHRs and clinical notes.

Step 02

Model Development

Designed and trained machine learning models using Scikit-learn and Pandas.

Step 03

Deployment & Monitoring

Deployed models on Google Cloud AI and set up monitoring for continuous improvement.

Result

Reduced patient readmission rates by 20% within six months.

Improved patient care through early identification of at-risk individuals.

Enhanced hospital efficiency by optimizing resource allocation.