Current Trends in Mass Communication(CTMC)

School of Computer Science and Engineering, Geeta University, India

Publications

• Research Article   
  Unified Diagnostic Intelligence: RESTful Integration of Validated Clinical Data and Machine Learning for Heart Health Prediction
  Author(s): Neha Bansal and Bhawna Singla*
  
  Heart disease remains one of the leading causes of death globally, with early prediction being crucial for timely intervention and improved patient outcomes. However, existing predictive systems are often constrained by fragmented, non-standardized clinical data across diagnostic centers. This paper presents a RESTful framework for heart disease prediction that leverages validated clinical data and state-of-the-art machine learning (ML) models. The system integrates data collection via a user-friendly website, validation using Pydantic models, and a FastAPI-based RESTful API for scalable, asynchronous data ingestion. Data undergoes rigorous validation at both frontend and backend levels before being preprocessed and transformed for machine learning. The ML pipeline includes imputation, scaling, and encoding of numeric and categorical features, followed by model selection usi.. Read More»
  

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