Moletest (Scotland) Ltd has over 10 years of experience in developing the technical, clinical and regulatory programmes of nomela®.

The initial analytical system (2013) used AI, trained from publicly available library images and a large pre-determined group of algorithms, with fuzzy logic to make the assessment for malignancy. However, when made available to the public on-line, the system was found to be unreliable because users took poor quality images.

The analysis engine was replaced (2014) by five selected proprietary signal-processing algorithms in nomela®, an image capture and analysis system for use by trained medical professionals, embedded on a single-application iPad. Although found to be easy to use by dermatology nurses in clinical studies the performance of the analytical engine was considered lower than expectation.

The analytical engine used in nomela® v6 (2024) is a machine-learning AI system, selected after substantial and rigorous comparative testing. Training and validation was made on images derived from a basic set of c1000, all with consent and definitive histopathology results obtained in a clinical study. The nomela® v6 AI system is uniquely enhanced by patented automated edge detection to ignore skin surrounding the lesion under test.