readmission

SQL analysis of hospital readmission rates using patient data

Your own 🤖 Doctor

Analyzing and predicting 30-day readmission to help hospitals intervene and prevent readmission to reduce costs

Power BI: ML-scored hospital readmission predictor — targeting $26B in preventable readmissions

Machine-learning model that predicts hospital readmission risk from structured clinical data (Python, Jupyter, Docker).

COVID-19 30-day readmission risk pipeline — EHR cohort construction, ML scoring, Streamlit care manager dashboard

Blake's Haas Capstone Project - Patient Readmissions Prediction

"SQL analysis of 30-day hospital readmission patterns using the UCI Diabetes 130-US Hospitals dataset (MySQL, joins, CTEs, window functions)"

Healthcare Analytics project using MySQL and Power BI to identify factors driving hospital readmissions.

Predicting the readmission of Diabetic patients using Machine Learning based on various factors.

30-day hospital readmission risk on 99,343 real inpatient encounters. Why AUC 0.66 is still useful, why balanced class weights break calibration, and what a care-management team actually gets.

Analysed 10 years of diabetic patient hospital records using MySQL and Tableau to identify the primary risk factors driving 30-day readmissions, age, diagnosis type, and discharge disposition.