Hemkiran, S and Mohammad Mudasir, War and Aadhithiyan, K S and Kabilan, K (2024) Web-Based Patient Health Management System with Doctor Recommendations and Medicine Alternatives using Machine Learning. In: 2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), Coimbatore, India.
Full text not available from this repository.Abstract
Web-Based Patient Health Management System with Doctor Recommendations and Medicine Alternatives depicts a novel doctor appointment system that unites simplicity with sophisticated technology, featuring a Random Forest Classifier model to boost healthcare services. Another advantageous component is the inclusion of a specific pharmacy area, enabling efficient drug administration tracking. Confirmation emails are sent upon successful appointment bookings, keeping individuals updated on upcoming visits. The platform also encompasses a multifaceted disease prediction mechanism powered by the Random Forest Classifier's predictive capabilities, assisting physicians in delivering accurate diagnoses and targeted therapy recommendations[15]. Integrating of these elements results in a comprehensive strategy for managing patient health. By emphasizing user-friendliness and advanced technology, the system aims to elevate both patient satisfaction and healthcare provider productivity. Employing machine learning techniques within medical settings can lead to enhanced appointment scheduling efficiency and diagnostic precision, ultimately benefiting patients through improved care outcomes.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | Appointment; Classifier models; Health management systems; Machine-learning; Patient health; Random forest classifier; Recommendation; Symptom; Tailored guidance; Web based |
Subjects: | C Computer Science and Engineering > Health Care, Disease C Computer Science and Engineering > Websites C Computer Science and Engineering > Machine Learning |
Divisions: | Computer Science and Engineering |
Depositing User: | Dr Krishnamurthy V |
Date Deposited: | 28 Sep 2024 09:01 |
Last Modified: | 28 Sep 2024 09:02 |
URI: | https://ir.psgitech.ac.in/id/eprint/1195 |