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Using a Natural Language Processing and Machine Learning Algorithm Program to Analyze Inter-Radiologist Report Style Variation and Compare Variation Between Radiologists When Using Highly Structured Versus More Free Text Reporting.

Current problems in diagnostic radiology Oct 9, 2018
PURPOSE: To use a natural language processing and machine learning algorithm to evaluate inter-radiologist report variation and compare variation between radiologists using highly structured versus more free text reporting.
Humans Machine Learning Software Natural Language Processing Research Report Radiology Information Systems
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Decision-Tree Based Meta-Strategy Improved Accuracy of Disorder Prediction and Identified Novel Disordered Residues Inside Binding Motifs.

International journal of molecular sciences Oct 7, 2018
Using computational techniques to identify intrinsically disordered residues is practical and effective in biological studies. Therefore, designing novel high-accuracy strategies is always preferable when existing strategies have a lot of room for im...
Humans Neural Networks, Computer Software Intrinsically Disordered Proteins Sequence Analysis, Protein
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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine Oct 5, 2018
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...
RNA Software Pattern Recognition, Automated Algorithms Female False Positive Reactions Humans Male Reproducibility of Results Lung Neoplasms Diagnosis, Computer-Assisted Sequence Analysis, RNA Deep Learning Gene Expression Regulation, Neoplastic Stomach Neoplasms Supervised Machine Learning Breast Neoplasms
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Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology Sep 28, 2018
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...
Female Animals Male Neuronal Plasticity Calcium Neurogenesis Neural Networks, Computer Models, Neurological Stochastic Processes Sensory Receptor Cells Software Models, Statistical Superior Colliculi Retina Zebrafish
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WEADE: A workflow for enrichment analysis and data exploration.

PloS one Sep 28, 2018
Data analysis based on enrichment of Gene Ontology terms has become an important step in exploring large gene or protein expression datasets and several stand-alone or web tools exist for that purpose. However, a comprehensive and consistent analysis...
Software Systems Analysis Data Interpretation, Statistical Internet Gene Regulatory Networks Workflow Genomics Gene Ontology Databases, Genetic
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Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

Journal of clinical monitoring and computing Sep 27, 2018
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiolog...
Child, Preschool Child Intensive Care Units, Pediatric Monitoring, Physiologic Signal Processing, Computer-Assisted Heart Rate Critical Care Blood Pressure Oxygen Infant, Newborn Systole Humans Reproducibility of Results Respiratory Rate Machine Learning Sensitivity and Specificity Heart Arrest Software Infant Critical Illness
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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.

Genomics, proteomics & bioinformatics Sep 27, 2018
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Amino Acid Sequence Nitrosation Reproducibility of Results Proteins Humans Deep Learning Amino Acids Neural Networks, Computer Internet Software
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Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

American journal of physiology. Renal physiology Sep 26, 2018
Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput and consistent manner. Neither untrained individuals nor computers are presently capable of identify...
Mice, Transgenic Microscopy Image Interpretation, Computer-Assisted Pattern Recognition, Automated Species Specificity Predictive Value of Tests Biopsy Workflow Kidney Glomerulus Female Reproducibility of Results Animals Male Disease Models, Animal Mice, Inbred C57BL Machine Learning Kidney Diseases Diagnosis, Computer-Assisted Software Rats Humans Automation, Laboratory Phenotype
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Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Journal of clinical monitoring and computing Sep 24, 2018
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...
Signal Processing, Computer-Assisted Colonic Neoplasms Patient Compliance Patient Readmission Monitoring, Intraoperative Treatment Outcome Infusions, Intravenous Data Interpretation, Statistical Medical Informatics Colorectal Surgery Ketorolac Humans Artificial Intelligence Machine Learning Inflammatory Bowel Diseases Reproducibility of Results Pilot Projects Software Algorithms
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A universal SNP and small-indel variant caller using deep neural networks.

Nature biotechnology Sep 24, 2018
Despite rapid advances in sequencing technologies, accurately calling genetic variants present in an individual genome from billions of short, errorful sequence reads remains challenging. Here we show that a deep convolutional neural network can call...
Neural Networks, Computer Software Animals Genomics Polymorphism, Single Nucleotide Humans DNA Mutational Analysis Genome, Human INDEL Mutation Genotype Sequence Analysis, DNA Mammals High-Throughput Nucleotide Sequencing
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