AIMC Topic: Melanoma

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Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology Jun 24, 2020
Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contain...
Humans Machine Learning Cytokines Prognosis Middle Aged Peptides ROC Curve Neoplasm Staging Neoplasm Metastasis Female Melanoma Biomarkers, Tumor Male
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Gene Expression Profile Prediction in Uveal Melanoma Using Deep Learning: A Pilot Study for the Development of an Alternative Survival Prediction Tool.

Ophthalmology. Retina Jun 18, 2020
Humans Melanoma Biomarkers, Tumor Anterior Eye Segment Uveal Neoplasms Uveal Melanoma Transcriptome Deep Learning Pilot Projects Gene Expression Regulation, Neoplastic
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Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesions.

European journal of cancer (Oxford, England : 1990) Jun 10, 2020
BACKGROUND: Convolutional neural networks (CNNs) have shown a dermatologist-level performance in the classification of skin lesions. We aimed to deliver a head-to-head comparison of a conventional image analyser (CIA), which depends on segmentation a...
Humans Deep Learning Adolescent Predictive Value of Tests Image Interpretation, Computer-Assisted Aged Aged, 80 and over Young Adult Adult Cross-Sectional Studies Male Middle Aged Diagnosis, Computer-Assisted Melanoma Skin Neoplasms Dermoscopy Reproducibility of Results Databases, Factual Prospective Studies Prognosis Female
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An Efficient Skin Cancer Diagnostic System Using Bendlet Transform and Support Vector Machine.

Anais da Academia Brasileira de Ciencias May 29, 2020
Skin is the outermost and largest organ of the human body that protects us from the external agents. Among the various types of diseases affecting the skin, melanoma (skin cancer) is the most dangerous and deadliest disease. Though it is one of the d...
Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Support Vector Machine Humans Melanoma Skin Neoplasms Dermoscopy
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A deep learning system for differential diagnosis of skin diseases.

Nature medicine May 18, 2020
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of sk...
Folliculitis Nurse Practitioners Keratosis, Seborrheic Warts Dermatitis, Seborrheic Physicians, Primary Care Alaska Natives Native Hawaiian or Pacific Islander Black or African American Eczema Acne Vulgaris Asian Photography Skin Diseases Hispanic or Latino Telemedicine White People Indians, North American Psoriasis Diagnosis, Differential Dermatologists Female Melanoma Skin Neoplasms Carcinoma, Basal Cell Male Middle Aged Deep Learning Carcinoma, Squamous Cell Adult Humans
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Technological advances for the detection of melanoma: Advances in diagnostic techniques.

Journal of the American Academy of Dermatology Apr 26, 2020
Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patien...
Microscopy, Confocal Biomedical Technology Dielectric Spectroscopy Photography Melanoma Skin Neoplasms Dermoscopy Imaging, Three-Dimensional Humans Machine Learning
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New Auxiliary Function with Properties in Nonsmooth Global Optimization for Melanoma Skin Cancer Segmentation.

BioMed research international Apr 13, 2020
In this paper, an algorithm is introduced to solve the global optimization problem for melanoma skin cancer segmentation. The algorithm is based on the smoothing of an auxiliary function that is constructed using a known local minimizer and smoothed ...
Humans Neural Networks, Computer Algorithms Melanoma Skin Neoplasms Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Melanoma, Cutaneous Malignant
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A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Apr 1, 2020
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) staining would save money, time, and reduce tissue co...
Databases, Factual Melanoma Skin Neoplasms Staining and Labeling Immunohistochemistry Melanocytes SOXE Transcription Factors Humans Neural Networks, Computer Machine Learning Algorithms
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Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders.

Sensors (Basel, Switzerland) Mar 11, 2020
In this research, we present a semi-supervised segmentation solution using convolutional autoencoders to solve the problem of segmentation tasks having a small number of ground-truth images. We evaluate the proposed deep network architecture for the ...
Deep Learning Skin Supervised Machine Learning Image Interpretation, Computer-Assisted Humans Algorithms Melanoma Sensitivity and Specificity Nevus Melanocytes
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DePicT Melanoma Deep-CLASS: a deep convolutional neural networks approach to classify skin lesion images.

BMC bioinformatics Mar 11, 2020
BACKGROUND: Melanoma results in the vast majority of skin cancer deaths during the last decades, even though this disease accounts for only one percent of all skin cancers' instances. The survival rates of melanoma from early to terminal stages is mo...
Humans Deep Learning ROC Curve Area Under Curve Databases, Factual Melanoma Skin Neoplasms Dermoscopy
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