Published Bachelor of Computer Applications • 2025

Clinic Management System with Disease Pattern Analysis and Smart Suggestion Engine

healthcare system medical data suggestion engine disease pattern analysis clinic management

menu_book Abstract

This project introduces a smart Clinic Management System designed to simplify patient record handling while providing intelligent disease pattern detection and suggestion capabilities. Built using modern web technologies, the system analyzes recurring symptoms, patient history, and diagnosis patterns to assist clinics in identifying potential health issues early.

By integrating a lightweight pattern-finding algorithm, the system helps healthcare providers observe trends such as common seasonal diseases, frequently reported symptoms, or recurring diagnostic paths. It also suggests probable conditions based on patient symptoms, supporting faster and more informed decision-making. The goal is to improve operational efficiency and enhance patient care quality for small and medium-sized clinics.

The Clinic Management System with Disease Pattern Detection is a web-based platform for managing patients, appointments, treatments, prescriptions, and medical history. The system further incorporates analytical logic to identify symptom patterns and provide rule-based or data-driven suggestions to doctors.

Key Objectives

  • Digitalize clinic operations

  • Maintain accurate patient medical history

  • Detect recurring disease patterns

  • Provide symptom-based suggestions to assist doctors

  • Improve treatment efficiency and decision-making

Main Features

  • Patient Registration & Medical History

  • Appointment & Doctor Scheduling

  • Symptom Input & Pattern Detection

  • Smart Suggestion Engine (Rule-Based or ML-Lite)

  • Prescription & Treatment Record Module

  • Admin Dashboard for Reports & Analytics

  • Disease Trend Visualization (e.g., seasonal, frequent symptoms)

  • Secure Backend with PHP/Node.js & MySQL/MongoDB

Outcome

The system enhances clinical workflows by combining management functions with intelligent disease pattern analysis. It supports faster diagnosis, reduces manual workload, and adds advanced decision-support features—making it an excellent and impactful final-year BCA project.

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