Identified factors causing chronic kidney disease. Built the predictive model to identify subjects, who could be potentially affected by CKD. Interpretation of the statistical model to estimate the impact of each factor leading to CKD.
Built the Predictive Model to estimate the price of treatment given the clinical factors at the time of admission. Feature engineering of clinical factors to identify portential predictors for the price estimate.
The Machine learning based research study aims at examining and monitoring the various depression markers by analyzing the tweets of self-declared depression patients on Twitter. Temporal analysis of pre and post diagnosis of depressed individuals.