Early Detection of Skin Cancer

1963 ◽  
Vol 34 (6) ◽  
pp. 593-600
Author(s):  
Harold Plotnick ◽  
Hermann Pinkus
Keyword(s):  
2010 ◽  
Vol 18 (4) ◽  
pp. 417-420 ◽  
Author(s):  
Peter J. Anderson ◽  
John B. Lowe ◽  
Warren R. Stanton ◽  
Kevin P. Balanda

Author(s):  
Pawan Sonawane ◽  
Sahel Shardhul ◽  
Raju Mendhe

The vast majority of skin cancer deaths are from melanoma, with about 1.04 million cases annually. Early detection of the same can be immensely helpful in order to try to cure it. But most of the diagnosis procedures are either extremely expensive or not available to a vast majority, as these centers are concentrated in urban regions only. Thus, there is a need for an application that can perform a quick, efficient, and low-cost diagnosis. Our solution proposes to build a server less mobile application on the AWS cloud that takes the images of potential skin tumors and classifies it as either Malignant or Benign. The classification would be carried out using a trained Convolution Neural Network model and Transfer learning (Inception v3). Several experiments will be performed based on Morphology and Color of the tumor to identify ideal parameters.


2020 ◽  
Vol 44 (2) ◽  
pp. 111-115 ◽  
Author(s):  
Monika Janda ◽  
Anne E. Cust ◽  
Rachel E. Neale ◽  
Joanne F. Aitken ◽  
Peter D. Baade ◽  
...  

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Cindy L. Lamerson ◽  
Kristina Eaton ◽  
Joel L. Sax ◽  
Mohammed Kashani-Sabet

This study examined whether patient-identified melanomas were more advanced than dermatologist-identified tumors at routine clinic visits, and whether a personal or family history of skin cancer was associated with patterns of detection. A retrospective chart review was performed on melanoma patients (N=201) in a private dermatology clinic. Variables included age, gender, pattern of detection (i.e., patient or a board certified dermatologist), personal or family history of skin cancer, skin type, and previous sun exposure, as well as tumor location and severity. Dermatologist-diagnosed melanomas were less invasive (P<0.0005), and more likely present on the chest, back, and legs (P<0.01). Conversely, patient-identified lesions were more likely to occur on the face, neck and scalp, be associated with younger patients, and a family history of melanoma, but not other types of skin cancer (P<0.01). In a post-hoc analysis examining these factors as predictors of tumor invasiveness, only diagnostic source was significant. Specifically, dermatologist-identified tumors were significantly less invasive than patient-identified tumors. Although age, family history, and tumor location played roles in the early detection of melanomas, the most important factor was diagnostic source. Thus, board-certified dermatologists play a key role in the early detection of malignant melanoma.


2019 ◽  
Vol 57 (10) ◽  
pp. e33
Author(s):  
Miss Molly Harte ◽  
Mr Greg Knepil
Keyword(s):  

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