MetaOptima Team Awarded The ISIC 2018 Challenge Disease Classification Prize

by The DermEngine Team on Mar 25, 2019

MetaOptima’s Research and Development team has been honoured with the ISIC 2018 Challenge for Skin Cancer Classification award. The team successfully earned first, second, and third place within the competition for their three submissions.

1. What is the ISIC Challenge?
The goal of ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection is to help participants develop image analysis tools to enable the automated diagnosis of melanoma from dermoscopic images.

The ISIC 2018 challenge consisted of three tasks, with the MetaOptima Team focusing on the third titled “Task 3: Disease Classification”. The objective was to design a method  that can automatically diagnose an image of a skin lesion as one of the following seven skin diseases: melanoma, melanocytic nevus, basal cell carcinoma, actinic keratosis, benign keratosis, dermatofibroma, or a vascular lesion.

A set of 10015 images and diagnoses were provided for the training of algorithms, however participants had the option to use any other external data.  For the final evaluation, participants made predictions on a held-out set of 1512 images and submitted them to an online system to be scored. The metric used for scoring was the accuracy of the classifier on each of the classes averaged together, known as “mean recall” or “balanced accuracy”.

DermEngine algorithms were awarded the ISIC 2018 Award for their accuracy in skin cancer disease classification.2. MetaOptima’s achievements
MetaOptima’s submissions ranked first, second, and third for its approaches titled Top 10 Models Averaged (88.5%), Meta Ensemble (88.2%), and Best Single Model (87.1%) respectively. Primary Metric Values indicate that the company’s entries ranked notably higher when compared to submissions with a difference of 2.9% between MetaOptima’s top ranking approach and the fourth placed entry.

Although this model does not constitute a real-world use case as presented, the approach offers substantial clinical value as it proved the possibility to obtain high classification accuracy by ensembling multiple models trained for a 7-class skin lesion classification. The outcome of this competition was especially encouraging because it demonstrates how our software’s AI-based algorithms possess significant potential to support medical professionals with evidence-based clinical decisions for enhanced patient care. Challenges such as these truly highlight the future for artificial intelligence in dermatology in how can be utilized to empower doctors and care providers to supply patients with improved  treatment options.

ISIC 2018 Challenge for Skin Cancer Classification top three positions for MetaOptima Technology Inc.

What the future holds
An important milestone to celebrate, this is also the perfect motivation for the continuous development of new breakthroughs focused on the provided quality of care to patients. To this regard, MetaOptima has been actively involved in the participation and execution of several projects both individually and in strategic partnerships. To learn more about recent initiatives, follow the links below:

-The MetaOptima Team
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Topics: Dermatology AI Big Data Health Data Advanced Dermatology Data Analytics in Healthcare AI In Healthcare EMR Dermatology EMR Dermatology Software Machine Learning Dermatology EMR Software ISIC2018 Skin Imaging System