Optimizing Patient Identification And Appointment Management with Iris Recognition Technology

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.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-12-13
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.32312
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Patient Identification And Appointment Management with Iris Recognition Technology

Plasin Francis Dias, PARVEENBANU N NADAF -, VIJAYALAXMI KALAL -
International Journal For Multidisciplinary Research
Biometric Identification and Security
article

Optimizing Patient Identification And Appointment Management with Iris Recognition Technology

Plasin Francis Dias, PARVEENBANU N NADAF -, VIJAYALAXMI KALAL -
article en

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.

International Journal For Multidisciplinary ResearchVol. 6(6)
Openalex Percentile: Top 74%
Biometric Identification and Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.