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@article{178951,
        author = {Priyanka Kalshetti and Ankita Narwade and Vedant Hirlekar and Parth Chitnis},
        title = {A Web-Based Telemedicine Approach for Remote Disease Prediction Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {9201-9206},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178951},
        abstract = {With the increasing demand for secure and 
efficient healthcare solutions, integrating biometric 
authentication and machine Learning-driven diagnosis 
has become crucial in telemedicine. This paper presents 
a hybrid approach that enhances healthcare 
accessibility 
by 
implementing 
fingerprint 
authentication alongside machine learning-based 
disease prediction for diabetes and skin diseases. The 
system ensures secure access through biometric 
authentication while leveraging Convolutional Neural 
Networks (CNNs) for skin disease detection and 
Support Vector Machines (SVMs) for diabetes 
prediction. The proposed solution integrates a web
based interface where users can securely log in using 
either a password or fingerprint authentication, 
ensuring robust security. Patient data, including 
medical history and symptoms, is processed using 
machine learning models to provide accurate disease 
predictions. The backend architecture incorporates a 
secure API layer that facilitates authentication, 
symptom-based diagnosis, and medical record storage. 
Our experimental results demonstrate the effectiveness 
of CNN for skin disease classification and SVM for 
diabetes prediction, achieving high accuracy. By 
combining biometric authentication with ML-powered 
diagnosis, this system enhances security, accuracy, and 
efficiency in remote healthcare services.},
        keywords = {Biometric Authentication, Patient Data  Management, Symptom Matching, Fingerprint  Recognition, Diabetes Prediction, Skin Disease  Classification, Machine Learning in Healthcare,  Telemedicine Security.},
        month = {June},
        }