AIMC Topic: Skin Neoplasms

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Dense Deconvolutional Network for Skin Lesion Segmentation.

IEEE journal of biomedical and health informatics Jul 25, 2018
Automatic delineation of skin lesion contours from dermoscopy images is a basic step in the process of diagnosis and treatment of skin lesions. However, it is a challenging task due to the high variation of appearances and sizes of skin lesions. In o...
Algorithms Skin Neoplasms Dermoscopy Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Machine learning model in melanoma.

The Lancet. Oncology Jun 7, 2018
Germany Clinical Competence Retrospective Studies Sensitivity and Specificity Humans Dermatologists Female Melanoma Male Machine Learning Skin Neoplasms Diagnosis, Computer-Assisted
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Automated Dermatological Diagnosis: Hype or Reality?

The Journal of investigative dermatology Jun 1, 2018
Algorithms Skin Neoplasms Deep Learning Humans
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Interpretation of the Outputs of a Deep Learning Model Trained with a Skin Cancer Dataset.

The Journal of investigative dermatology Jun 1, 2018
Humans Algorithms Skin Neoplasms Deep Learning Skin
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Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features.

IEEE journal of biomedical and health informatics May 1, 2018
The presence of certain clinical dermoscopic features within a skin lesion may indicate melanoma, and automatically detecting these features may lead to more quantitative and reproducible diagnoses. We reformulate the task of classifying clinical der...
Humans Skin Neoplasms Dermoscopy ROC Curve Skin Neural Networks, Computer Databases, Factual Melanoma Image Interpretation, Computer-Assisted
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Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

IEEE/ACM transactions on computational biology and bioinformatics Apr 26, 2018
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent years. Most of the existing methods assume that the cost of intervention at each state and time point,...
Tumor Suppressor Protein p53 Proto-Oncogene Proteins c-mdm2 Wnt-5a Protein Models, Genetic Bayes Theorem Models, Biological Algorithms Melanoma Skin Neoplasms Computational Biology Gene Expression Regulation, Neoplastic Gene Expression Profiling Gene Regulatory Networks Humans Machine Learning Software
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Acral melanoma detection using a convolutional neural network for dermoscopy images.

PloS one Mar 7, 2018
BACKGROUND/PURPOSE: Acral melanoma is the most common type of melanoma in Asians, and usually results in a poor prognosis due to late diagnosis. We applied a convolutional neural network to dermoscopy images of acral melanoma and benign nevi on the h...
Early Detection of Cancer Skin Neoplasms Humans Skin Dermoscopy Neural Networks, Computer Hand Image Interpretation, Computer-Assisted Sensitivity and Specificity Melanoma Foot
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DermaKNet: Incorporating the Knowledge of Dermatologists to Convolutional Neural Networks for Skin Lesion Diagnosis.

IEEE journal of biomedical and health informatics Feb 16, 2018
Traditional approaches to automatic diagnosis of skin lesions consisted of classifiers working on sets of hand-crafted features, some of which modeled lesion aspects of special importance for dermatologists. Recently, the broad adoption of convolutio...
Image Interpretation, Computer-Assisted Skin Neoplasms Dermoscopy Skin Neural Networks, Computer Algorithms Databases, Factual Melanoma Humans
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Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Female Skin Neoplasms Granuloma, Pyogenic Aged Keratosis, Actinic Biopsy Adult Lentigo Skin Male Image Processing, Computer-Assisted Datasets as Topic Aged, 80 and over Humans Diagnosis, Differential Keratosis, Seborrheic Young Adult Software Warts Middle Aged Predictive Value of Tests False Positive Reactions Photography Deep Learning ROC Curve Area Under Curve
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Predicting non-melanoma skin cancer via a multi-parameterized artificial neural network.

Scientific reports Jan 26, 2018
Ultraviolet radiation (UVR) exposure and family history are major associated risk factors for the development of non-melanoma skin cancer (NMSC). The objective of this study was to develop and validate a multi-parameterized artificial neural network ...
Sensitivity and Specificity Humans Diagnostic Tests, Routine Male Decision Support Techniques Middle Aged Neural Networks, Computer Early Diagnosis Female ROC Curve Skin Neoplasms
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