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Development of a Next-Generation AI-Powered Skin Health Platform

atta.systems

Medical

Information technology

Artificial Intelligence

Challenges in Maintaining and Enhancing a Leading Medical AI Application

SkinVision, a CE-certified medical application for skin health, requires ongoing development to address challenges related to maintaining accuracy and reliability of AI algorithms, ensuring robust data security and privacy, optimizing image quality across diverse devices and lighting conditions, enhancing user experience for a health-sensitive audience, ensuring scalability and performance with growing user base, and navigating evolving global regulatory landscapes. The existing codebase requires modernization and expansion to accommodate new features and maintain compliance.

About the Client

A leading European medical technology company specializing in AI-powered skin health solutions, focused on early detection of skin cancer through mobile technology.

Project Goals

Enhance the accuracy and reliability of the AI-powered skin cancer risk assessment.
Strengthen data security and privacy measures to comply with evolving regulations (GDPR, HIPAA).
Improve image acquisition and processing algorithms to handle variations in smartphone cameras and lighting.
Redesign the user interface for improved usability and accessibility.
Scale the backend infrastructure to accommodate a growing user base and data volume.
Ensure ongoing compliance with global medical device regulations.
Develop and integrate new features to expand the platform's capabilities (e.g., personalized skincare recommendations, integration with telehealth services).

Functional Requirements

Mobile image acquisition (iOS and Android).
AI-powered skin lesion analysis and risk assessment.
User account management and secure data storage.
Reporting and analytics (user activity, risk trends).
Integration with external databases (e.g., medical records, dermatology resources).
User-friendly interface with accessibility features.
Secure data transmission and storage compliant with HIPAA/GDPR.

Preferred Technologies

Swift (iOS)

Kotlin (Android)

Cloud-based backend (AWS, Azure, or GCP)

Python (for AI/ML algorithms)

Computer Vision libraries (e.g., OpenCV)

Secure data encryption (AES, TLS)

Integrations Required

Electronic Health Record (EHR) systems (optional)
Telehealth platforms (optional)
Payment gateways (for premium features)
Third-party image analysis APIs (for enhanced capabilities)

Key Non-Functional Requirements

High accuracy and reliability (minimize false positives/negatives).
Scalability to support a large and growing user base.
High performance and fast response times.
Robust security and data privacy.
Compliance with all applicable medical regulations (e.g., HIPAA, GDPR).
Maintainability and ease of updates.

Expected Business Impact

This project is expected to significantly enhance SkinVision's market position by improving the accuracy and reliability of its AI-powered skin health platform. This will lead to increased user trust, improved patient outcomes, and expanded market reach. Furthermore, modernization of the codebase will reduce maintenance costs and enable faster development of new features, ensuring long-term competitiveness in the rapidly evolving medical technology landscape. The enhanced platform will also provide a foundation for future expansion into related areas of skin health and personalized medicine.