Application of Machine Learning and its use in determining Sepsis Prediction

Application of Machine Learning and its use in determining Sepsis Prediction

Prashanth Kumar Alay1

1Department of Health Management and Informatics, MU, School of Medicine.

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Abstract - Sepsis is a potentially life-threatening and serious condition that occurs when an infection spreads across the body and triggers a widespread inflammatory response. It has a significantly high death rate, especially for patients in the ICU. Early detection and treatment of sepsis is necessary. Machine learning models for sepsis detection can be trained on a variety of data sources, such as electronic health records (EHRs), vital signs, laboratory test results, and demographic information. Exploratory Data analysis was performed using different pre-processing techniques. To classify the disease, the Random Forest Classifier is used, and comparison also performed among various Classifiers like MLP, KNN, etc.

Key Words: Sepsis Prediction, Random Forest Classifier, vital signs.