AIMC Topic: Machine Learning

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Machine learning approaches for pathologic diagnosis.

Virchows Archiv : an international journal of pathology Jun 20, 2019
Machine learning techniques, especially deep learning techniques such as convolutional neural networks, have been successfully applied to general image recognitions since their overwhelming performance at the 2012 ImageNet Large Scale Visual Recognit...
Humans Machine Learning Pathology, Clinical
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Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

Circulation. Arrhythmia and electrophysiology Jun 20, 2019
BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed whether machine learning (ML) could predict CRT response beyond current guidelines.
Machine Learning Decision Support Techniques Retrospective Studies Clinical Decision-Making Humans Practice Guidelines as Topic Middle Aged Heart-Assist Devices Baltimore Risk Assessment Heart Transplantation Disease Progression Heart Failure Ohio Time Factors Cardiac Resynchronization Therapy Recovery of Function Progression-Free Survival Female Predictive Value of Tests Patient Selection Risk Factors Aged Male Ventricular Function, Left Stroke Volume Echocardiography
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Recognition of early and late stages of bladder cancer using metabolites and machine learning.

Metabolomics : Official journal of the Metabolomic Society Jun 20, 2019
INTRODUCTION: Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and ...
Area Under Curve Neoplasm Staging Amino Acids Proto-Oncogene Proteins c-akt Glycine Galactose ErbB Receptors Insulin ROC Curve Urinary Bladder Neoplasms Metabolic Networks and Pathways Machine Learning Humans Software Biomarkers, Tumor
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Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR Jun 20, 2019
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...
Population Surveillance Disease Susceptibility ROC Curve Genetic Predisposition to Disease Models, Theoretical Prognosis Female Adult Breast Neoplasms Middle Aged Risk Assessment Big Data Humans Machine Learning Algorithms Precision Medicine
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MetaNN: accurate classification of host phenotypes from metagenomic data using neural networks.

BMC bioinformatics Jun 20, 2019
BACKGROUND: Microbiome profiles in the human body and environment niches have become publicly available due to recent advances in high-throughput sequencing technologies. Indeed, recent studies have already identified different microbiome profiles in...
Models, Theoretical Support Vector Machine Databases, Genetic Area Under Curve Algorithms Phenotype ROC Curve Microbiota Metagenomics Humans Neural Networks, Computer Machine Learning
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Ten quick tips for effective dimensionality reduction.

PLoS computational biology Jun 20, 2019
Databases, Factual Computational Biology Models, Statistical Signal Processing, Computer-Assisted Humans Machine Learning
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Reconstruction of long-distance bird migration routes using advanced machine learning techniques on geolocator data.

Journal of the Royal Society, Interface Jun 19, 2019
Geolocators are a well-established technology to reconstruct migration routes of animals that are too small to carry satellite tags (e.g. passerine birds). These devices record environmental light-level data that enable the reconstruction of daily po...
Models, Biological Machine Learning Seasons Animals Animal Migration Geographic Information Systems Swallows
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Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans.

Cerebrovascular diseases (Basel, Switzerland) Jun 19, 2019
Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more likely to have good outcomes and ranges from 0 (no collaterals) to 3 (complete collaterals). In this stu...
Computed Tomography Angiography Cerebral Angiography Stroke Collateral Circulation Clinical Decision-Making Humans Blood Flow Velocity Patient Selection Predictive Value of Tests Machine Learning Thrombectomy Automation Triage Prognosis Cerebrovascular Circulation Radiographic Image Interpretation, Computer-Assisted Middle Cerebral Artery
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On the improvement of reinforcement active learning with the involvement of cross entropy to address one-shot learning problem.

PloS one Jun 19, 2019
As a promising research direction in recent decades, active learning allows an oracle to assign labels to typical examples for performance improvement in learning systems. Existing works mainly focus on designing criteria for screening examples of hi...
Machine Learning Models, Theoretical Entropy
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A Probabilistic Synapse With Strained MTJs for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems Jun 18, 2019
Spiking neural networks (SNNs) are of interest for applications for which conventional computing suffers from the nearly insurmountable memory-processor bottleneck. This paper presents a stochastic SNN architecture that is based on specialized logic-...
Humans Neural Networks, Computer Action Potentials Machine Learning Probability Neuronal Plasticity Synapses
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