The AI-based software Moleanalyzer pro allows a risk-of-malignancy evaluation. It works with a deep learning algorithm: The human ability to learn from examples and experiences is transferred to the computer. Artificial neural networks enable complex machine learning that is similar to biological learning processes. The larger, better and more unique the data basis is, the more intelligent the system becomes in a short period of time, thanks to continuous training.
FotoFinder Moleanalyzer pro has currently the largest data collection of dermoscopic images, including their associated diagnosis. The continuous "feeding" of the algorithm succeeds thanks to years of cooperation with physicians from all over the world!
For many people, the everyday use of artificial intelligence (AI) still seems like science fiction. However, as pioneer in this field, FotoFinder is already incorporating AI in dermatological practices with the Moleanalyzer pro expert system and, more recently, with the handyscope 3 App. The Moleanalyzer pro offers unique possibilities in the assessment and follow-up of melanocytic and non-melanocytic lesions, ranging from their initial analysis all the way to a Second Opinion Service.
The deep learning algorithm supports dermatologists in the earliest possible detection of skin cancer. Simple. Accurate. Validated. In future, the use of AI in dermoscopy will not only improve the quality of early skin cancer detection but will also facilitate a worldwide network of physicians to ensure fast and easy access to the most modern and uniform diagnostic standards. In the event of any remaining doubt, the FotoFinder Second Opinion Service combines AI with “human intelligence”.
"Man against machine" (2018), Hänssle et al.
"Man against machine reloaded" (2020), Hänssle et al.
"Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition" (2021), Winkler et al.
"Melanoma recognition by a deep learning convolutional neural network-Performance in different melanoma subtypes and localisations" (2020), Winkler et al.
"The Use of Non-Invasive Imaging Techniques in the Diagnosis of Melanoma: A Prospective Diagnostic Accuracy Study" (2020), MacLellan et al.
"Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesion" (2020), Sies et al.
"Human–computer collaboration for skin cancer recognition" (2020), Tschandl et al.
"Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas" (2019), Fink et al.
The optional AI Score is the perfect support for risk assessment of melanocytic and non-melanocytic skin lesions. Whether melanoma in situ or basal cell carcinoma, the accuracy is impressive! To use the potential of artificial intelligence, you need Internet access and a "PRO" account in the FotoFinder Hub.
Artificial Intelligence - Advantage through Data
AI is THE trend in dermatology worldwide. While countless projects are still in the prototype phase, the Moleanalyzer pro is already validated.
The FotoFinder Contribution Team is looking for contributors for further training of the AI algorithm. Contact us if you are interested in a cooperation!
The AI score of the Moleanalyzer pro was evaluated by Prof. Dr. med. Holger Hänßle and Dr. med. Christine Fink at the Heidelberg University, Department of Dermatology.
The corresponding studies „Man against machine“ (2018) & "Man against machine reloaded" (2020) prove the high accuracy of the score.
Moleanalyzer pro offers you the option to get a second opinion from experienced world-class dermoscopists. Prof. H. Peter Soyer, Prof. Andreas Blum or Prof. Rainer Hofmann-Wellenhof will give you valuable expert advice at the click of a mouse. All you need is Internet access and an account in the FotoFinder Hub.
Artificial Intelligence in skin cancer prevention