Project Name: ICU Survived
We set out to identify trends and drivers affecting the survival rates of patients in the ICU. We utilized data manipulation tools such as pandas to transform our data, then applied ML algorithms from scikit-learn to create a model able to outperform the industry standard. Our model helps hospitals identify high risk patients, but additionally can be used in the identification of cases where the patient had a likely chance of survival but something went wrong.
Dedicated and passionate, I strive to improve everyday. A product that is not understandable is not a good product, and I make an effort to make anything I'm working on interesting to others.
finding the "ah-ha!" moment inside of the data and finding ways to bring that insight to others!
Remote | San Antonio, TX
Dedicated, passionate, and driven
Python, scripting, analysis