New technology using AI to tell the difference between harmless moles and dangerous melanomas has hit the market.

Created by FotoFinder Systems, Moleanalyzer pro is a portal that lets physicians confirm their skin cancer diagnosis using evaluation techniques, combining specialist expertise with AI and including the option of receiving a second opinion from international skin cancer experts.

FotoFinder Systems Global Brand Director Kathrin Niemela told HITNA that the technology aims to aid skin cancer diagnoses.

According to the Cancer Council Australia, every year skin cancers account for around 80 per cent of all newly diagnosed cancers in Australia, with GPs seeing more than a million patients per year for skin cancer.

In addition, the Australian Government identified that there were 14,320 new cases of melanoma skin cancer diagnosed in 2018, accounting for 10.4 per cent of all new cancer cases diagnosed.

“The earlier skin cancer is detected, the better the prognosis. The leisure behaviour of sunbathing in many parts of the world makes early detection of skin cancer more important worldwide,” Niemela said.

FotoFinder Systems first calculates and compares size, diameter and structure of moles and quantifies their percentage deviations.

Moleanalyzer pro works with deep learning. Its Convolutional Neural Network was ‘trained’ with a large data collection of dermoscopic images and corresponding diagnoses. Through growing experience and its own autonomous rules, it then distinguishes between benign and malignant lesions.

“Moleanalyzer pro features the possibility to manually evaluate lesions according to acknowledged checklists and optionally contains an innovative algorithm based on AI, allowing a risk-of-malignancy evaluation,” Niemela said.

“In the last few years, the new algorithm has been trained with a large number of dermoscopic images. FotoFinder Systems has an international network of partners who contribute to the training of the algorithm with their pictures of histologically proven lesions.”

The analysis then determines a risk assessment score of both melanocytic and non-melanocytic skin lesions, allowing physicians to verify their diagnoses.

FotoFinder Systems is working towards making this AI score available for doctors on mobile devices.

“When this technology becomes available for mobile devices, rural physicians, for example, who practice far away from clinics or specialist centers can use the Moleanalyzer pro's deep learning algorithm on their mobile phones to get a second opinion on their diagnosis of skin lesions,” Niemela said.

The application also allows physicians to request a second opinion from skin cancer experts.

“The AI represents a ‘silent virtual colleague’ that delivers a virtual opinion simply, uncomplicatedly and at any time. But together with the human experience delivered by the optional second opinion service, the tool helps to increase diagnostic accuracy.”

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According to Niemela, a man-against-machine study involving 58 dermatologists from 17 nations found that whereas the experts correctly identified 86.6 of malignant skin tumours, Moleanalyzer pro successfully detected 95 per cent.

In addition, the technology identified 82.5 per cent of benign naevi correctly, while the experts identified 71.3 per cent as benign.

However, Niemela said the technology was not expected to replace specialists.

“As fascinating as AI is, it cannot take the place of human experience in the matter of skin cancer. AI will increasingly find its way into dermatology and mole examinations by supporting physicians, not by replacing them,” Niemela said.

“Doctors need to combine total body mapping with video documentation of single moles and AI-based evaluation. The combination of these three elements are the pillars of early skin cancer detection. Only a physician with profound knowledge and experience can map this complex process.

“In addition, patients do not want to do away with doctors under any circumstances and want to combine high-tech solutions with specialist competence.”

And the future potential for AI in skin cancer detection is huge.

“The aim of AI is to bundle global knowledge and consistent diagnostic standards – independent of the practice location – all over the world. The combination of human experience and AI can contribute to a drastic improvement in diagnostic accuracy in early skin cancer detection, with the potential for almost 100 per cent accuracy,” Niemela added.