Project Name: ICU Survived - Predicting ICU Survival
We are building a machine learning model, which will predict the probability of survival in the ICU. Additionally, it helps in identifying unexpected patient outcomes so we can improve clinical decision making. We used data from over 90k patients, from 200 hospitals, across 8 countries. We accomplished this with extensive EDA, feature engineering, statistical testing, and Classification ML algorithms - Logistic Regression, LightGBM, and XGBoost - to identify the best predictors in this imbalanced dataset.
I'm an effective communicator, that can articulate actionable insights throughout the org chart. I'm a problem-solver at my core, with polished soft skills, and an ever-growing set of data science technical skills.
approaching the data with purpose, while finding insights and actionable solutions.
San Antonio, TX | Remote Work
Adaptable, Determined, and Energetic
Open communication, Purposeful, Client Facing
