• Pavurnika S
• Manjusri J
• Mrs.Nivethitha Devi M

Melanoma, a form of skin cancer arising from melanocytes, presents a considerable public health challenge globally due to its rising incidence and potential for metastasis. Early detection plays a pivotal role in improving patient outcomes, and recent advancements in technology have spurred innovative approaches to enhance diagnostic accuracy. The overview of cutting-edge techniques, focusing on the integration of Machine learning (ML),Augmented Reality(AR) and imaging technologies for melanoma cancer detection. By harnessing advanced ML algorithms, the system attains heightened precision in identifying melanoma, crucial for early intervention. Augmented reality further enriches the diagnostic process, providing clinicians with enhanced visualization tools. The synergy of ML and AR not only elevates accuracy but also opens avenues for innovative methodologies in skin cancer detection. This proposed system contributes to the evolving landscape of medical technology, offering a promising solution to improve melanoma detection and subsequent patient outcomes.

Technological advancements, Diagnostic accuracy, Machine learning (ML),Augmented Reality (AR)Imaging technologies ,Visualization tools, Patient outcomes.

"A COMPREHENSIVE GUIDE TO MELANOMA CANCER DETECTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.g539-g544, January-2024, Available :http://www.jetir.org/papers/JETIR2401665.pdf

"A COMPREHENSIVE GUIDE TO MELANOMA CANCER DETECTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. ppg539-g544, January-2024, Available at : http://www.jetir.org/papers/JETIR2401665.pdf