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May is Skin Cancer Awareness Month – prevention is essential!
The annual Skin Cancer Awareness Month appeals: Skin cancer screening is the key to the earliest possible detection - even in times of COVID-19.
State-of-the-art video dermoscopy for more safety in the matter of skin
The days have passed when dermatologists examined moles with the naked eye or a simple magnifying glass. Today, the use of computer-assisted examination methods for skin cancer screening is a benchmark in every dermatological practice like the FotoFinder vexia with the integrated video dermatoscope medicam 1000s. The system enables mole mapping of (suspicious) lesions not only by taking overview images but also by storing pin-sharp and standardized micro images, which make even the smallest skin changes visible in comparison. The FotoFinder medicam 1000s comes with exchangeable front caps, which can be changed for disinfection after each patient.
For the new edition of the FotoFinder vexia, purist design was combined with proven functionality and stability. The result: aesthetics in every detail and perfectly matched components. For even more safety during the skin check.
AI assistant for skin analysis
The expert software Moleanalyzer pro supports dermatologists in the evaluation of suspicious skin lesions and brings Artificial Intelligence (AI) directly into the dermatologist‘s practice via the optional AI Score (Artificial Intelligence Score).
The Software combines AI with medical expertise and contains an algorithm based on the Artificial Intelligence of a neural network that allows a pre-assessment of malignancies. For this reason, the lesion – as individual image or in the image comparison – is classified on a color scale by an automatically generated AI Score between 0 and 1. Moleanalyzer pro tool supports the pre-assessment of melanocytic and non-melanocytic lesions with one of the most powerful deep learning algorithms evaluated in clinical trials up to now.**
** Man against machine”, Annals of Oncology, https://doi.org/... & “Man against machine reloaded”, Annals of Oncology, https://doi.org/...
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