Tennessee Patent of the Month – October 2024
Cortina Health, Inc. has unveiled a groundbreaking system that leverages artificial intelligence to revolutionize dermatological care. This innovative technology classifies skin color, analyzes diseased skin, and generates personalized treatment plans—all from the convenience of a user’s mobile device. By integrating AI with biometric data, the system enables precise skin assessments that were previously only possible through specialist consultation.
The system begins by capturing an image of a user’s skin and combining it with biometric information, such as medical history, to classify skin tone accurately. Unlike traditional methods relying on manual analysis, this approach employs advanced AI models to determine classifications like the Fitzpatrick skin score, ensuring consistency and eliminating subjective errors.
For diagnosing skin conditions, users can upload images of affected areas. The system evaluates these images, cross-referencing medical records and inputting the data into AI classifiers. This process not only identifies potential conditions but also assesses their severity, paving the way for early detection of issues like skin cancer. The AI continuously refines its model, improving diagnostic accuracy over time.
In treatment planning, Cortina Health’s system shines by tailoring regimens to individual needs. Drawing on historical medical data, user-provided information, and outcomes from similar cases, it selects optimal treatments. Progress is tracked through follow-up images, enabling real-time adjustments to the plan, maximizing the likelihood of successful outcomes.
By democratizing access to high-quality dermatological care, Cortina Health bridges the gap between patients and specialists. Its blend of AI precision, cloud-based processing, and user-friendly interfaces empowers individuals to take charge of their skin health while providing healthcare professionals with invaluable diagnostic tools. This innovation represents a new era of accessible, data-driven dermatology.
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