International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 02 | Feb 2025
p-ISSN: 2395-0072
www.irjet.net
Intelligent Healthcare Delivery with a Multi-Algorithm Ensemble Approach and Java Spring Boot Integration Jagadish N1, Darshan V A2, Gautham Gopal Kulal3, Himamshu B S4, Karthik5 1Assistant Professor, Dept. of IS Engineering, Acharya Institute of Technology, Bengaluru, India 2Student, Dept. of IS Engineering, Acharya Institute of Technology, Bengaluru, India 3Student, Dept. of IS Engineering, Acharya Institute of Technology, Bengaluru, India
4Student, Dept. of IS Engineering, Acharya Institute of Technology, Bengaluru, India 5Student, Dept. of IS Engineering, Acharya Institute of Technology, Bengaluru, India
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Abstract - This paper presents Intelli Health Care, a unified
The platform supports multi-role functionality, allowing patients to book appointments, doctors to create prescriptions and schedule lab tests, and lab technicians to upload reports. Automated email notifications ensure that patients receive timely updates about their appointments, prescriptions, and lab results, enhancing communication and reducing manual effort. One of the standout features of Intelli Health Care is its multi-algorithm ensemble approach for disease prediction, which combines Decision Trees, Random Forests, and Naïve Bayes to analyze symptoms and provide reliable diagnoses. Additionally, the platform integrates the Llama API to deliver detailed information about medicine composition and usage, empowering doctors to make informed decisions. By combining these advanced features, Intelli Health Care addresses key pain points in healthcare delivery, such as delayed diagnostics, inefficient workflows, and limited access to medical information [2].
Java Spring Boot application that leverages machine learning for disease prediction and automated healthcare workflows. The system employs a multi-algorithm ensemble approach, combining Decision Tree, Random Forest, and Naïve Bayes classifiers to improve diagnostic reliability. It features rolebased access for doctors, patients, and lab technicians, enabling appointment scheduling, prescription generation, and lab test management. Additionally, AI integration allows real-time medicine composition lookup via the Llama API. Automated email notifications streamline patient communication, ensuring efficient healthcare delivery. The proposed system enhances decision-making, reduces manual workload, and provides an intelligent, scalable solution for digital healthcare transformation. Key Words: healthcare informatics, machine learning for disease prediction, multi-algorithm ensemble approach, java spring boot, ai-driven diagnosis, medical decision support system, automated healthcare workflows, electronic health records.
1.1 Motivation The motivation behind this project stems from the growing need for intelligent healthcare solutions that can handle the increasing complexity of medical data while providing userfriendly interfaces for all stakeholders. Existing systems often lack integration between AI-driven diagnostics and practical healthcare workflows, leading to fragmented and inefficient processes. Intelli Health Care aims to overcome these limitations by offering a unified platform that integrates AI, ML, and web technologies to deliver a comprehensive healthcare solution. This paper presents the design, implementation, and evaluation of the Intelli Health Care platform. The following sections discuss the system architecture, the AI models used for disease prediction, the integration of the Llama API for medicine information retrieval, and the platform’s multi-role functionality. The results demonstrate the platform’s effectiveness in improving healthcare workflows, enhancing diagnostic accuracy, and providing a user-friendly experience for patients, doctors, and lab technicians. By leveraging the power of AI and web technologies, Intelli Health Care represents a significant step forward in the evolution of intelligent healthcare systems [5].
1. INTRODUCTION The healthcare industry is undergoing a transformative shift, driven by the integration of advanced technologies such as artificial intelligence (AI), machine learning (ML), and webbased platforms. These innovations aim to address critical challenges in healthcare delivery, including inefficiencies in patient-doctor communication, delayed diagnostics, and the growing demand for personalized care. In this context, the development of intelligent systems that streamline healthcare workflows, enhance diagnostic accuracy, and improve patient outcomes has become a priority. This paper introduces Intelli Health Care, a web-based platform designed to bridge the gap between patients, doctors, and lab technicians by leveraging cutting-edge technologies to create a seamless and efficient healthcare ecosystem. The Intelli Health Care platform is built on a robust backend framework using Java Spring Boot, ensuring scalability, security, and efficient data management [1]. It incorporates Python-based AI models for predictive analytics, enabling accurate disease prediction based on patient symptoms [4].
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