AIMC Topic: Melanoma

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Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks.

IEEE journal of biomedical and health informatics Dec 25, 2017
Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diagnosis of melanoma. However, this task is challenging due to significant variations of lesion appearances across different patients. This challenge is ...
Skin Neoplasms Dermoscopy Humans Deep Learning Algorithms Skin Databases, Factual Image Interpretation, Computer-Assisted Melanoma
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Effect of dacarbazine on CD44 in live melanoma cells as measured by atomic force microscopy-based nanoscopy.

International journal of nanomedicine Dec 18, 2017
CD44 ligand-receptor interactions are known to be involved in regulating cell migration and tumor cell metastasis. High expression levels of CD44 correlate with a poor prognosis of melanoma patients. In order to understand not only the mechanistic ba...
Quantum Dots Kinetics Dacarbazine Microscopy, Atomic Force Animals Actins Melanoma Cell Line, Tumor Hyaluronan Receptors Mice Tubulin Cell Survival Single Molecule Imaging
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Salinomycin-loaded lipid-polymer nanoparticles with anti-CD20 aptamers selectively suppress human CD20+ melanoma stem cells.

Acta pharmacologica Sinica Dec 14, 2017
Melanoma is the deadliest type of skin cancer. CD20+ melanoma stem cells (CSCs) are pivotal for metastasis and initiation of melanoma. Therefore, selective elimination of CD20+ melanoma CSCs represents an effective treatment to eradicate melanoma. Sa...
Particle Size Drug Carriers Polyethylene Glycols Aptamers, Nucleotide Lecithins Humans Xenograft Model Antitumor Assays Nanoparticles Melanoma Antigens, CD20 Animals Neoplastic Stem Cells Pyrans Antineoplastic Agents Mice, Inbred BALB C
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From word models to executable models of signaling networks using automated assembly.

Molecular systems biology Nov 24, 2017
Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to b...
Tumor Suppressor Protein p53 Proto-Oncogene Proteins p21(ras) Proto-Oncogene Proteins B-raf Vemurafenib Sulfonamides Indoles Enzyme Inhibitors Drug Resistance, Neoplasm Neural Networks, Computer Models, Genetic Humans Skin Neoplasms Computer Simulation Signal Transduction Antineoplastic Agents Language Natural Language Processing Cell Line, Tumor Melanoma DNA Damage Gene Expression Regulation, Neoplastic
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Melanoma segmentation based on deep learning.

Computer assisted surgery (Abingdon, England) Oct 18, 2017
Malignant melanoma is one of the most deadly forms of skin cancer, which is one of the world's fastest-growing cancers. Early diagnosis and treatment is critical. In this study, a neural network structure is utilized to construct a broad and accurate...
Algorithms Melanoma Skin Neoplasms Reproducibility of Results Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Early Detection of Cancer Melanoma, Cutaneous Malignant
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Machine learning and melanoma: The future of screening.

Journal of the American Academy of Dermatology Oct 6, 2017
Humans Machine Learning Melanoma Skin Neoplasms Dermoscopy Sensitivity and Specificity Early Detection of Cancer
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Employing decomposable partially observable Markov decision processes to control gene regulatory networks.

Artificial intelligence in medicine Jul 18, 2017
OBJECTIVE: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).
Databases, Genetic Markov Chains Artificial Intelligence Melanoma Skin Neoplasms Gene Expression Profiling Transcriptome Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic Humans
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and cell-based analyses reveal strong divergence between prediction and observation of T-cell-recognized tumor antigen T-cell epitopes.

The Journal of biological chemistry May 23, 2017
Tumor exomes provide comprehensive information on mutated, overexpressed genes and aberrant splicing, which can be exploited for personalized cancer immunotherapy. Of particular interest are mutated tumor antigen T-cell epitopes, because neoepitope-s...
Models, Immunological Protein Refolding T-Lymphocytes, Cytotoxic Expert Systems Oligopeptides Immunogenicity, Vaccine Mice, Transgenic Antigens, Neoplasm Vaccines, Synthetic Membrane Proteins Neoplasm Proteins Epitopes HLA-A2 Antigen Protein Stability Reproducibility of Results Mice, Knockout Animals Humans Peptide Fragments Computational Biology Artificial Intelligence Cancer Vaccines Cells, Cultured Melanoma
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Dermatologist-level classification of skin cancer with deep neural networks.

Nature Jan 25, 2017
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of ski...
Dermatologists Keratinocytes Datasets as Topic Automation Neural Networks, Computer Photography Humans Melanoma Cell Phone Skin Neoplasms Nevus Reproducibility of Results Keratosis, Seborrheic
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Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.

IEEE transactions on medical imaging Dec 1, 2016
We develop a novel method for classifying melanocytic tumors as benign or malignant by the analysis of digital dermoscopy images. The algorithm follows three steps: first, lesions are extracted using a self-generating neural network (SGNN); second, f...
Skin Neoplasms Humans Dermoscopy Neural Networks, Computer Image Interpretation, Computer-Assisted Algorithms Melanoma
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