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Skin Cancer - Crossref

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Last Updated: 27 April 2022

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Computer-aided diagnosis of skin cancer based on soft computing techniques

Abstract Skin cancer is a form of cancer in which malignant cells are established in skin tissue. However, skin cancer is a deadly disease, and early detection of the condition aids the therapists in avoiding this disease. An automated computer-aided approach is introduced in the present study for the early diagnosis of skin cancer. Following image noise reduction based on median filter in the first stage, a new image segmentation based on the convolutional neural network optimized by satin bowerbird optimization has been introduced, and the confusion matrix has shown its effectiveness.

Source link: https://doi.org/10.1515/med-2020-0131


Optimization of the Convolutional Neural Networks for Automatic Detection of Skin Cancer

Abstract Convolutional neural networks are a branch of deep learning and have been converted into one of the most common techniques in various industries, particularly medical imaging. In this article, a meta-heuristic optimized CNN classifier is used for pre-trained network models for visual datasets with the intention of identifying skin cancer images. However, there are several ways to optimize neural networks' learning process, and there are few studies on deep learning based neural networks and their applications. The new method is then compared with ten commonly used classifiers on two skin cancer databases, including DermIS Digital Database Dermquest Database.

Source link: https://doi.org/10.1515/med-2020-0006


Optimal diagnosis of the skin cancer using a hybrid deep neural network and grasshopper optimization algorithm

Abstract: When skin cells divide abnormally, it can lead to a tumor or abnormal lymph fluid or blood. Skin cancer is more straightforward to diagnose than other cancers because its signs can be seen with the naked eye. To achieve greater diagnostic results, this paper recommends the use of a new non-destructive testing technique based on the AlexNet and Extreme Learning Machine networks. The proposed method with 98% accuracy and 93% sensitivity is then compared to several other state-of-art technologies, and the results revealed that the simulated method with 98% accuracy and 93% sensitivity had the highest effectiveness.

Source link: https://doi.org/10.1515/med-2022-0439


Skin Cancer Detection Using Infrared Thermography: Measurement Setup, Procedure and Equipment

Infrared thermography technology has progressed dramatically in recent years, and it is gaining renewed attention in the medical sector for applications in skin tissue identification applications. An summary of various measurement methods, thermal excitation methods, and infrared camera equipment is included in this literature review. By choosing an appropriate cooling system, infrared camera, and optimized measurement setup, thermal images of skin lesions can be enhanced thermal images of skin lesions.

Source link: https://doi.org/10.3390/s22093327


Tumor necrosis factor receptor 1-mediated signaling is required for skin cancer development induced by NF-κB inhibition

Skin growth and epidermal growth control are two primary factors in skin formation and epidermal growth control. Both the inflammatory and tumor necrosis factor receptor 1-null responses are blocked when crossing K5-I B mice into a tumor necrosis factor receptor 1-null background. K5-I B mice deficient in the IL-1 receptor type 1 exhibit inflammation and squamous cell carcinomas, illustrating the specificity of the block. B mice lacking the IL-1 receptor type 1 exhibit inflammation and squamous cell carcinomas. Our findings show a crucial role of local Tnfr1-mediated signaling and associated inflammatory response cooperating with repressed keratinocyte NF-B signaling in skin cancer formation.

Source link: https://doi.org/10.1073/pnas.0307106101


Skin Cancer-Associated S. aureus Strains Can Induce DNA Damage in Human Keratinocytes by Downregulating DNA Repair and Promoting Oxidative Stress

After a challenge with sterile culture supernatant isolated from four S. aurus clinical strains isolated from AK and SCC, we investigated whether S. auus can have cancer-promoting effects on skin cells by RNA sequencing and shotgun proteomics on primary human keratinocytes. Keratinocytes of two of the S. aurian strains were induced to overexpress biomarkers associated with skin carcinogenesis and increased the expression of enzymes related to reduced skin barrier function. A significant relationship was found between the concentration of S. aureus phenol soluble modulin toxins in secretome and the secretome-induced level of oxidative stress and genotoxicity in keratinocytes. These results, when taken together, show that lesion-associated clinical isolates of S. aurus may have cancer-promoting genes in keratinocytes, which may be relevant to skin oncogenesis.

Source link: https://doi.org/10.3390/cancers14092143


GHK, the Human Skin Remodeling Peptide, Induces Anti-Cancer Expression of Numerous Caspase, Growth Regulatory, and DNA Repair Genes

In recent reports, GHK was discovered to switch gene expression from a diseased state to a healthier state for certain cancers and chronic obstructive pulmonary disease. The Broad Institute's Connectivity Map reported that GHK, one of the 1,309 bioactive molecules tested, reversed the expression of 70% of 54 genes overexpressed genes in studies of aggressive, metastatic human colon cancer. In several cultured human cancer lines, GHK also reactivates programmed cell death. GHK increased gene expression in 6 of the 12 human caspase genes that trigger programmed cell death, leading to programmed cell death. GHK edited the pattern of gene expression in 28 other genes in a way that might be expected to reduce cancer formation in 28 other genes. A previous analysis revealed that a copper peptide plus ascorbic acid inhibited Ehrlich assays cancer in mice. These findings point to the fact that GHK may have the ability to prevent or minimize cancer growth.

Source link: https://doi.org/10.6000/1927-7229.2014.03.02.2

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions