Melanoma, otherwise known as malignant melanoma is the most dangerous skin cancer that we know of due to its potential to metastasize to other parts of the body including the liver, the lungs, bones and the brain. The most common patient groups are men over the age of 50, and women below the age of 30. The mechanism by which melanoma develops is due to damage to the skin DNA that goes unrepaired, triggering events that lead to rapid proliferation...
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Melanoma is an autosomal dominant disease which means that if you are to inherit it, the person before you would have had to have not one but two copies of the gene. If the melanoma is inherited it is called “familial malignant melanoma. If one of your parents had the two copies then you have a 50-50 chance of getting it. According to cancer.net, “Overall, about 8% of people newly diagnosed with melanoma have a first-degree relative with melanoma.” Also...
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Melanoma Background Melanoma in the early years was described as a benign mole that continued to grow and could be recognized by an irregular shape and discoloration of the mole (Sober et al., 1979). These cancer cells were well known for their ability to spread around the body quickly and avoid the therapeutic treatment, creating a dangerous situation (Li et al., 2001). When detected early, Melanoma could be removed successfully by a surgical procedure, but when metastasized, the cancer cells...
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Abstract— Skin diseases such as Melanoma and Carcinoma are often quite hard to detect at an early stage and it is even harder to classify them separately. Recently, it is well known that the most dangerous form of skin cancer among the other types of skin cancer is melanoma because it is much more likely to spread to other parts of the body if not diagnosed and treated early. In order to classify these skin diseases, “Support Vector Machine (SVM)”...
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Abstract: Automated melanoma recognition in using image processing technique from the available dermoscopic images in deep learning is difficult task because of the contrast and variation of melanoma in skin. It is mainly a non-invasive method so that it cannot contact with skin more forcefully. To overcome the disadvantages this paper proposes a method using very deep convolutional neural networks (CNNs).on comparing with older version of methods, in that lower-level features of CNN is employed. For more accurate classification in...
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Abstract Cancer treatments have been advancing over the previous decade because of the urgent need to identify new therapeutics. Melanoma accounts for only 4% of all dermatologic cancers, but it accounts for almost 80% of the deaths recorded from skin cancer because of its ability of deep invasion and spreading as well as Melanoma tumor cells were able to effectively block chemotherapy which arose the need for new Recent studies has shown that kinases play a crucial role in various...
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Abstract Skin cancer is caused due to irregular growth of cells. There are three major types of skin cancer- Melanoma, Basal, and Squamous cell Carcinoma. Among the three the most dangerous form is Melanoma. If it is left untreated, it leads to the spreading of all over the body including organs. However, the early stage detection of Melanoma is really helpful to cure it. Computer vision can be used for the medical image diagnosis and it has been proved by...
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Diseases of the Skeletal, Integumentary, and Nervous Systems The human body is made up of nine systems at the organ system level. These nine systems are made up of organs that have certain structures that promote functioning together, and similar functions and the systems working together constitute an organism. Diseases that affect three of these nine systems, the skeletal system, the integumentary system, and the nervous system is the focus of this essay. Skeletal System Disease: Osteoporosis Epidemiology and Causes...
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Abstract — Melanoma is the deadliest form of skin lesion which is a severe disease globally. Early detection of melanoma using medical images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging task. Since the joint use of image enhancement techniques and deep convolutional neural network (DCNN) has demonstrated proven success, the joint techniques could have discriminatory power on skin lesion diagnosis as well. To this hypothesis, we propose the aggregation algorithm for skin lesion...
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