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kin cancer is considered one of the most common type of cancer in severalcountries. Due to the difficulty and subjectivity in the clinical diagnosis ofskin lesions, Computer-Aided Diagnosis systems are being developed for assistexperts to perform more reliable diagnosis. The clinical analysis and diagnosisof skin lesions relies not only on the visual information but also on thecontext information provided by the patient. This work addresses the problem ofpigmented skin lesions detection from smartphones captured images. In additionto the features extracted from images, patient context information wascollected to provide a more accurate diagnosis. The experiments showed that thecombination of visual features with context information improved final results.Experimental results are very promising and comparable to experts.

Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data