Sai Mahidhar Reddy Byreddy

Dedicated and results-driven professional with a strong background in Health Informatics. Proficient in leveraging cutting-edge technology and data analysis techniques to optimize healthcare systems, improve patient outcomes, and enhance overall operational efficiency.

Predictive Modeling of Life Expectancy Using Global Health Statistics

• Developed predictive models using logistic regression, SVM, and Naive Bayes to identify key factors influencing life expectancy across countries.
• Performed extensive data analysis and visualization using Python to uncover insights from global health statistics.
• Contributed to model evaluation, visualization, and reporting to provide evidence-based recommendations on improving longevity.

Stratification of Cervical Cancer Risk Using Clinical Datasets

• Leveraged Python to conduct robust statistical analysis on clinical dataset, examining interrelationships between cervical cancer incidence and influential risk factors including age, contraception, and smoking.
• Developed and validated machine learning models to accurately predict cervical cancer likelihood based on input demographics, enabling data-driven identification of high-risk groups for targeted prevention and early intervention.