International Journal For Multidisciplinary Research

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Optimizing Patient Identification And Appointment Management with Iris Recognition Technology

Author(s) PARVEENBANU N NADAF, PLASIN FRANCIS DIAS, VIJAYALAXMI KALAL
Country India
Abstract The proposed project outlines the advancement of a web application that integrates iris recognition technology with a patient appointment management system. The application uses Convolutional Neural Networks for accurate iris detection, enhancing patient identification. It includes features for user registration, secure login, appointment scheduling, and doctor management. Patients who upload their iris images are identical with their previous medical records, allowing the system to present a list of relevant specialists based on their medical history. Patients can then select a specialist and book an appointment directly with that doctor. The backend is built using Flask and data is stored in an SQLite database. This setup ensures that appointment details and doctors' prescriptions are carefully recorded and maintained. By combining iris recognition with traditional appointment management, the system streamlines the booking process, improves patient identification, and maintains comprehensive medical records, thus enhancing the efficiency of healthcare services.
Keywords Dataset of iris, deep learning algorithm convolutional neural network, patient details
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-13
Cite This Optimizing Patient Identification And Appointment Management with Iris Recognition Technology - PARVEENBANU N NADAF, PLASIN FRANCIS DIAS, VIJAYALAXMI KALAL - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32312
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32312
Short DOI https://doi.org/g8wkpt
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