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

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

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

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

Blake's Haas Capstone Project - Patient Readmissions Prediction

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

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

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.