Corona Virus EDA & Prediction Model

Developed an end-to-end Streamlit dashboard analyzing and visualizing COVID-19 clinical data (219K+ records) with interactive filters for Diagnosis, Gender and Death.

Identified a 33.4% death rate among patients, underscoring critical mortality patterns and risk factors.

Built and integrated a machine learning model (Recall: 74%) to predict COVID-19 diagnosis based on patients’ health conditions.

Discovered that 61.4% of patients were non-hypertensive, emphasizing the need for targeted health education.