International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 11 | Nov 2024
p-ISSN: 2395-0072
www.irjet.net
Personalized Healthcare System Using Machine Learning Aryan Beluse1, Soham Dhavale2, Atharva Jaid3, Ayush Shinde4, Prathamesh Mahajan5, Noshir Tarapore6 1,2,3,4,5 LY B. Tech Computer Engineering, Science & Technology, Vishwakarma University, Pune, India –
411048
6Assistant Professor, Dept. of Computer Engineering, Vishwakarma University, Pune, India – 411048
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Doctors, on the other hand, gain access to a range of tools, including the ability to conduct specific analyses and suggest tailored treatment plans. By empowering healthcare providers with such tools, the platform enables more effective and personalized patient care. Additionally, the application promotes community involvement by including information about fitness events, NGOs, and charitable fundraisers, thereby fostering a comprehensive approach to health and wellness that goes beyond individual treatment and encourages preventive and community-centered health initiatives.
Abstract - Health management has become increasingly
complex with the rise of lifestyle-related conditions, chronic diseases, and the need for personalized care. Despite a growing interest in preventive healthcare, many individuals struggle to access reliable, actionable health information tailored to their unique needs. This paper presents a comprehensive, machine-learning-based healthcare application designed to empower users with personalized health recommendations, including diet and exercise routines, symptom-based disease suggestions, and preventive measures. Through distinct user portals for patients and doctors, the platform enables customized care, allowing doctors to analyze patient data and offer personalized treatment plans. Our goal with this application is to create a holistic, accessible health management system that bridges the gap between patients and healthcare providers and offer personalized health recommendations using machine learning.
1.2 Need of Study This study addresses the growing need for personalized healthcare solutions, driven by the limitations of traditional, reactive healthcare models that often overlook preventive care. With rising awareness of chronic diseases and the importance of proactive health management, there is an urgent need for accessible, reliable sources of health information and tools that empower individuals to monitor and manage their well-being.
Key Words: Disease prediction, SVC, Random Forest, Naive bayes, Personalized recommendation
1.INTRODUCTION
This study proposes a comprehensive web application that centralizes health information, symptom tracking, and tailored health recommendations. For individuals in remote or underserved areas, the app provides essential resources, bridging the gap in access to healthcare by enabling digital storage and sharing of health data. This platform also supports healthcare providers by giving them access to patient records, facilitating personalized care, and simplifying appointment scheduling. Through its secure, data-protective infrastructure, this study highlights a solution that not only meets today’s healthcare needs but promotes preventive care and healthier lifestyles.
The increasing focus on preventive healthcare and personalized treatment has driven a demand for accessible digital health solutions that empower individuals to take control of their wellness. Traditional healthcare systems, while essential, often lack the capacity to provide tailored guidance on a regular basis, leading patients to search for health advice on various online platforms that may not be reliable or personalized. This project aims to address these challenges by developing an integrated healthcare application that combines personalized health recommendations, symptom-based disease prediction, and continuous health monitoring.
2. LITERATURE SURVEY
Our application offers separate login options for doctors and patients, allowing both user groups to access tools suited to their needs. For patients, the application provides personalized diet and lifestyle recommendations, preventive measures, and symptom-based suggestions to help them maintain or improve their health. Through QRenabled record-keeping, patients can easily update and access their health information, streamlining management of their health history.
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Impact Factor value: 8.315
The integration of technology in healthcare has led to the development of various digital tools designed to enhance patient care, streamline medical record management, and improve health outcomes through personalized recommendations. Research has shown that personalized healthcare applications, which offer individualized guidance based on a patient’s specific health profile, can significantly improve adherence to preventive measures and treatment plans.
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