New diagnostics for melanoma detection: from artificial intelligence to RNA microarrays

2012 ◽  
Vol 8 (7) ◽  
pp. 819-827 ◽  
Author(s):  
Verena Ahlgrimm-Siess ◽  
Martin Laimer ◽  
Edith Arzberger ◽  
Rainer Hofmann-Wellenhof
Keyword(s):  
Artificial Intelligence ◽  
Melanoma Detection ◽  
Rna Microarrays

AI-Enabled Support System for Melanoma Detection and Classification

2021 ◽  
Vol 10 (4) ◽  
pp. 58-75
Author(s):  
Vivek Sen Saxena ◽  
Prashant Johri ◽  
Avneesh Kumar
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Skin Lesion ◽  
Performance Metrics ◽  
Similarity Index ◽  
Skin Lesions ◽  
Machine Learning Algorithms ◽  
Lesion Area ◽  
Melanoma Detection ◽  
Grabcut Algorithm

Skin lesion melanoma is the deadliest type of cancer. Artificial intelligence provides the power to classify skin lesions as melanoma and non-melanoma. The proposed system for melanoma detection and classification involves four steps: pre-processing, resizing all the images, removing noise and hair from dermoscopic images; image segmentation, identifying the lesion area; feature extraction, extracting features from segmented lesion and classification; and categorizing lesion as malignant (melanoma) and benign (non-melanoma). Modified GrabCut algorithm is employed to generate skin lesion. Segmented lesions are classified using machine learning algorithms such as SVM, k-NN, ANN, and logistic regression and evaluated on performance metrics like accuracy, sensitivity, and specificity. Results are compared with existing systems and achieved higher similarity index and accuracy.

Artificial intelligence and melanoma detection: friend or foe of dermatologists?

2020 ◽  
Vol 81 (1) ◽  
pp. 1-5
Author(s):  
Maria Charalambides ◽  
Sonal Singh
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Skin Cancer ◽  
Early Diagnosis ◽  
Clinical Application ◽  
Future Development ◽  
The Public ◽  
Melanoma Detection ◽  
Melanoma Prognosis ◽  
Melanoma Prevention

The significance of early diagnosis for melanoma prognosis and survival cannot be understated. The public health benefits of melanoma prevention and detection have driven advances in diagnostics for skin cancer, particularly in the field of artificial intelligence. Evaluating the benefits and limitations of artificial intelligence in dermatology is paramount to its future development and clinical application.

Artificial Intelligence

2009 ◽  
Author(s):  
David L. Poole ◽  
Alan K. Mackworth
Keyword(s):  
Artificial Intelligence
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