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Machine Learning Analytics

Transforming Patient Care Through Machine Learning

Increasing utilization of medical machines by leveraging ML models to predict patient readmission rates


  • Help prevent the hospitalization/re-hospitalization of patients post dialysis by leveraging predictive analytics
  • Build a model to predict the likelihood of hospitalization for high-risk patients within 30, 60 & 90 days of treatment at the hospital
  • Facilitate optimal utilization of slots and related resources allocated to patients with higher propensity of hospitalization


  • Analyzed data captured during a patient visit, including demographic details, vitals diagnosis, lab tests, and medical conditions currently associated with the patient
  • Developed classification machine learning models to predict patient hospitalization rate using advanced ML and DL algorithm
  • Analyzed important features and derived new ones to augment the model performance
  • Interpreted the reason behind hospitalization of each patients predicted positive by the model using model interpretability techniques

Tools & Technologies

Python, Anaconda, Spyder, Sokit Learn

Key benefits

  • Predicted the likelihood of patients’ readmission with 72% ROC-AUC score
  • Increased utilization of dialysis slots by 70%
  • Helped client improve their rating by keeping a check on hospitalization of CKD patients
  • Made efficient utilization of resources by providing better care to high-risk patients
  • Substantial medical cost savings with the help of preventive care
Key benefits from machine learning - ACS Solutions