AI-Powered Facial Recognition for Secure Patient and Medical Staff Identification
Streamlining medical record accuracy with a user-friendly, web-based platform to improve healthcare data management.
AI-Powered Facial Recognition
Work
Developing a web-based platform and app to make healthcare records more accurate. Includes an AI-powered facial recognition feature.
Summary
Due to delivery challenges, the client initially relied on fingerprint verification to identify patients and medical staff — but they sought a more efficient method. Langate developed a HIPAA-compliant application using AWS, incorporating neural network and face liveness checks to enhance security and prevent fraud.
Project Scope
6
Month5
DevelopersTech Stack
Cloud Platform: AWS
Compliance: HIPAA
Mobile Application Development: iOS and Android
Language: Dart
Framework: Flutter
Find out how Langate developed a mobile application that supports multiple verification scenarios.
Langate created a web-based platform and mobile app for iOS and Android with AI-powered facial recognition. This enabled the client to prevent fraud and duplicate subjects in clinical databases. Overall, it contributes to more efficient healthcare database management.
The Client
Our client helps healthcare organizations store and manage clinical data more effectively through the prevention of duplicate subjects and key protocol violations. Their main aim is to facilitate accurate and safe data management while saving time and money for healthcare providers, researchers, and other stakeholders.
The Problem
The client needed help verifying participants to prevent duplicate and fraudulent enrollments. Initially, they used document verification and fingerprint technology, but these methods proved cumbersome and difficult to manage. They decided to pursue a more streamlined and efficient software-based solution to handle verification remotely and securely.
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The Challenge
Finding a Cost-Effective, Reliable Service Provider
The client’s main challenge was finding a cost-effective, reliable service provider to handle sensitive facial recognition data. Their initial attempt with another company failed, leading the client to seek out Langate.
Data Storage and HIPAA Compliance Issues
The project encountered difficulties with strict data storage regulations, especially those concerning HIPAA compliance.
Preventing Fraudulent Methods
A critical requirement was to ensure that the system couldn’t be easily deceived by fraudulent methods, such as using photos instead of live faces.
The Process
Our team began by exploring various data processing services, ultimately choosing AWS for its balance of cost-effectiveness and compliance capabilities. After presenting a demo that met the client’s needs, the development process focused on creating a robust system that incorporated face liveness checks to ensure that the person being verified was alive and physically present. The solution also had to be flexible enough to support multiple verification scenarios, from remote registration to in-person authentication.
The Solution
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Achievements and Future Plans
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Remote Verification
Participants receive an invitation via email and can complete the registration process from home. A neural network validates their face using five photos as required by AWS. -
In-Person Authentication
Participants can be verified through a web portal that evaluates their data to ensure they are eligible. -
Future Enhancements
Plans include adding a camera-based verification system for administrators and expanding the application’s capabilities with a complete mobile app and a new backend system.
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