Transforming Healthcare with AI: The Face mapping Success Story

Transforming Healthcare with AI: The Face mapping

Problem:

Healthcare has witnessed a paradigm shift with the rise of telemedicine. Yet, accurately assessing a patient's health through virtual consultations remained a challenge. In telemedicine, visual cues such as age, gender, skin conditions, and signs of aging are often vital for diagnosis. Harrier Systems recognized this challenge and set out to create a solution that would bridge this gap

Project Solution:

Face map is an AI-powered application designed to scan and analyze a patient's face during a telemedicine consultation. The core features include:

The app helps to self-diagnose your skin type,wrinkles, dark circles, skin aging, and more.
Our face mapping and skin analysis app analyzes the skin by using image processing. With the CV2 library, it detects faces and then finds the edges. This helps the dermatologists detect wrinkles.
Our team created a ResNET-50 model by feeding maximum images to get higher accuracy.
We used the Ktrain library, which enables the app to detectall skin types.
Additionally, the app allows patients to download their skin analysis report.

The Future:

Harrier Systems is committed to advancing Face map further. We are exploring additional features, such as emotion recognition and early disease detection, to empower healthcare providers and improve patient care.

Technology Environment:

Tensor flow/Resnet50 model

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