Smart Diagnosis: Symptom-based Disease Prediction Using Machine Learning

Abstract

The Rapid Developments In Smart Health Care Applications The Usage Of Machine Learning Models, Enhance The Quality Of Disease Prediction Process, The Outcome And The Accuracy. The Need For Classifying The Diseases From The Massive Data Collected From Health Care Infrastructure Is Difficult. The Datasets Are Not Similar And Structured. Various Challenges Faced By The Platform Users To Retrieve The Analysis Results Within The Time. The Need For Effective Processing Of Healthcare Data Is Demandable. The Proposed System Comprised Of Multiple Machine Learning Algorithm Comparisons To Evaluate The Performance Of Prediction Quality As Well As Classify The Electronic Health Care Records (EHR) Towards Various Disease Category. Leveraging The Predictive Capability Of The Proposed Model, The Comparison Towards Performance, Disease Formulation Is Evaluated. The Proposed System Is Implemented With Authorized Web Application Accessed By The Health Care Professionals, To Analyse The Diseases. The Quality Of Prediction Is Increased Towards The Quality Of Input Dataset And Preprocessing Quality.

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