AIMC Topic: Sensitivity and Specificity

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A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Computer methods and programs in biomedicine Oct 30, 2018
BACKGROUND AND OBJECTIVE: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detec...
Algorithms Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Computer Systems Models, Statistical Fundus Oculi Retinal Diseases Humans Neural Networks, Computer Machine Learning Retinal Vessels
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A neural network based model effectively predicts enhancers from clinical ATAC-seq samples.

Scientific reports Oct 30, 2018
Enhancers are cis-acting sequences that regulate transcription rates of their target genes in a cell-specific manner and harbor disease-associated sequence variants in cognate cell types. Many complex diseases are associated with enhancer malfunction...
Sequence Analysis, DNA Gene Expression Profiling Humans Cell Line Transcriptome Enhancer Elements, Genetic High-Throughput Nucleotide Sequencing ROC Curve Neural Networks, Computer Binding Sites Transposases Sensitivity and Specificity Computational Biology
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Rapid Quantification of Protein Particles in High-Concentration Antibody Formulations.

Journal of pharmaceutical sciences Oct 27, 2018
Current technologies for monitoring the subvisible particles that may be generated during fill-finish operations for protein formulations are cumbersome. Measurement times are generally too long for real-time analysis, and the high protein concentrat...
Freezing Fluorescent Dyes Anilino Naphthalenesulfonates Protein Aggregates Sensitivity and Specificity Microscopy, Fluorescence Chemistry, Pharmaceutical Particle Size Drug Compounding Immunoglobulins, Intravenous Antibodies, Monoclonal Calibration
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Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy Oct 25, 2018
BACKGROUND AND AIMS: Although erosions and ulcerations are the most common small-bowel abnormalities found on wireless capsule endoscopy (WCE), a computer-aided detection method has not been established. We aimed to develop an artificial intelligence...
Ulcer Adult Intestine, Small Pattern Recognition, Automated Deep Learning Jejunal Diseases Humans Inflammatory Bowel Diseases Sensitivity and Specificity Capsule Endoscopy Peptic Ulcer Neural Networks, Computer Female Male ROC Curve Duodenal Ulcer Software Aged Middle Aged Anti-Inflammatory Agents, Non-Steroidal Ileal Diseases Aged, 80 and over Area Under Curve
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Identifying substance use risk based on deep neural networks and Instagram social media data.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Oct 24, 2018
Social media may provide new insight into our understanding of substance use and addiction. In this study, we developed a deep-learning method to automatically classify individuals' risk for alcohol, tobacco, and drug use based on the content from th...
Alcoholism Risk-Taking Risk Assessment Deep Learning Social Media Substance-Related Disorders Humans Adult Sensitivity and Specificity
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A convolutional neural network for ECG annotation as the basis for classification of cardiac rhythms.

Physiological measurement Oct 24, 2018
OBJECTIVE: Electrocardiography is the most common tool to diagnose cardiovascular diseases. Annotation, segmentation and rhythm classification of ECGs are challenging tasks, especially in the presence of atrial fibrillation and other arrhythmias. Our...
Humans Supervised Machine Learning Neural Networks, Computer Atrial Fibrillation Sensitivity and Specificity Heart Rate Diagnosis, Computer-Assisted Artifacts Electrocardiography
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Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy Oct 22, 2018
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...
Image Processing, Computer-Assisted Spectrum Analysis, Raman Support Vector Machine Principal Component Analysis Tuberculosis Male Humans Middle Aged Female Adolescent Young Adult Child Adult Sensitivity and Specificity
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Deep neural network improves fracture detection by clinicians.

Proceedings of the National Academy of Sciences of the United States of America Oct 22, 2018
Suspected fractures are among the most common reasons for patients to visit emergency departments (EDs), and X-ray imaging is the primary diagnostic tool used by clinicians to assess patients for fractures. Missing a fracture in a radiograph often ha...
Humans Neural Networks, Computer Radiography Wrist Image Interpretation, Computer-Assisted Emergency Medicine Sensitivity and Specificity Diagnostic Errors Deep Learning Fractures, Bone Hospital Rapid Response Team
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Automated detection of cancer cells in effusion specimens by DNA karyometry.

Cancer cytopathology Oct 19, 2018
BACKGROUND: The average sensitivity of conventional cytology for the identification of cancer cells in effusion specimens is only approximately 58%. DNA image cytometry (DNA-ICM), which exploits the DNA content of morphologically suspicious nuclei me...
Cell Nucleus DNA, Neoplasm Image Cytometry Karyometry Humans Neoplasms Machine Learning Diagnosis, Computer-Assisted Sensitivity and Specificity Epithelium Aneuploidy
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Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning.

Scientific reports Oct 15, 2018
RNA binding protein (RBP) plays an important role in cellular processes. Identifying RBPs by computation and experiment are both essential. Recently, an RBP predictor, RBPPred, is proposed in our group to predict RBPs. However, RBPPred is too slow fo...
Databases, Protein Amino Acid Sequence Sequence Analysis, Protein Deep Learning Computational Biology RNA-Binding Proteins Proteome Neural Networks, Computer Machine Learning Algorithms Sensitivity and Specificity
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