Optimizing Neuro-Fuzzy and Colonial Competition Algorithms for Skin Cancer Diagnosis in Dermatoscopic Images
Researchers have developed an AI system to aid in skin cancer diagnosis using neuro-fuzzy and colonial competition algorithms. Applied to 560 dermatoscopic images from the ISIC database, the system achieved 94% accuracy in distinguishing malignant from benign lesions. This approach shows promise for early melanoma detection and supporting clinical diagnostics. AI
IMPACT This AI approach could improve early detection rates for melanoma, aiding clinicians in diagnosis.