Smart Diagnostics: Exploring AI-Based Models for Disease Forecasting and Timely Identification

Akshat Mishra; Alfi Naaz; Er. Sarika  Singh; Dr. Sadhana  Rana

Smart Diagnostics: Exploring AI-Based Models for Disease Forecasting and Timely Identification

Authors

Akshat Mishra Student, Department of CSE, Shri Ramswaroop Memorial College of Engineering and Management
Alfi Naaz Student, Department of CSE, Shri Ramswaroop Memorial College of Engineering and Management
Er. Sarika Singh Assistant Professor, Department of CSE, Shri Ramswaroop Memorial College of Engineering and Management
Dr. Sadhana Rana Assistant Professor, Department of CSE, Shri Ramswaroop Memorial College of Engineering and Management

Abstract

This paper proposes a novel system for predicting diseases, utilizing machine learning methods to facilitate early identification and elevate patient care quality. This study presents an advanced smart disease prediction system that harnesses machine learning to improve early diagnosis and optimize healthcare outcomes. As chronic and lifestyle-related diseases become more prevalent, conventional diagnostic approaches often struggle with speed and accuracy. To address these challenges, the proposed system employs the Random Forest algorithm to analyze patient symptoms and medical history for disease prediction. The dataset includes a diverse range of patient records, capturing symptom patterns and corresponding diagnoses. Experimental findings confirm the system’s effectiveness across various test scenarios, highlighting its potential to support healthcare professionals in making timely decisions and delivering personalized patient care

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Smart Diagnostics: Exploring AI-Based Models for Disease Forecasting and Timely Identification