AIMC Topic: Reproducibility of Results

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A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

IEEE transactions on bio-medical engineering Nov 24, 2015
UNLABELLED: This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a G...
Humans Neural Networks, Computer Adult Sensitivity and Specificity Male Diagnosis, Computer-Assisted Machine Learning Brain Female Reproducibility of Results Cognition Electroencephalography Methadone Opioid-Related Disorders Pattern Recognition, Automated
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Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PloS one Nov 24, 2015
Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biolog...
Machine Learning Algorithms Reproducibility of Results Geography DNA, Plant Genes, Plant Microsatellite Repeats Phylogeography Alleles Genotype Iran Computational Biology Genetic Variation Decision Trees Olea Bayes Theorem
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Optimism in Active Learning.

Computational intelligence and neuroscience Nov 23, 2015
Active learning is the problem of interactively constructing the training set used in classification in order to reduce its size. It would ideally successively add the instance-label pair that decreases the classification error most. However, the eff...
Attitude Uncertainty Databases, Factual Computer Simulation Reproducibility of Results Cluster Analysis Humans Machine Learning Algorithms
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Using Blood Indexes to Predict Overweight Statuses: An Extreme Learning Machine-Based Approach.

PloS one Nov 23, 2015
The number of the overweight people continues to rise across the world. Studies have shown that being overweight can increase health risks, such as high blood pressure, diabetes mellitus, coronary heart disease, and certain forms of cancer. Therefore...
Case-Control Studies Overweight Support Vector Machine Area Under Curve Models, Biological Humans Machine Learning Neural Networks, Computer Female Reproducibility of Results Male
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Improved Neural Signal Classification in a Rapid Serial Visual Presentation Task Using Active Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 20, 2015
The application space for brain-computer interface (BCI) technologies is rapidly expanding with improvements in technology. However, most real-time BCIs require extensive individualized calibration prior to use, and systems often have to be recalibra...
Signal Processing, Computer-Assisted Calibration Brain-Computer Interfaces Photic Stimulation Female Reproducibility of Results Young Adult Adult Male Middle Aged Adolescent Electroencephalography Humans Machine Learning Algorithms
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Hand Rehabilitation Learning System With an Exoskeleton Robotic Glove.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Nov 19, 2015
This paper presents a hand rehabilitation learning system, the SAFE Glove, a device that can be utilized to enhance the rehabilitation of subjects with disabilities. This system is able to learn fingertip motion and force for grasping different objec...
Humans Machine Learning Software Equipment Design Reproducibility of Results Hand Therapy, Computer-Assisted Sensitivity and Specificity Equipment Failure Analysis User-Computer Interface Exoskeleton Device Persons with Disabilities Robotics
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Beyond Classification: Structured Regression for Robust Cell Detection Using Convolutional Neural Network.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Nov 18, 2015
Robust cell detection serves as a critical prerequisite for many biomedical image analysis applications. In this paper, we present a novel convolutional neural network (CNN) based structured regression model, which is shown to be able to handle touch...
Sensitivity and Specificity Regression Analysis Cytological Techniques Neural Networks, Computer Algorithms Reproducibility of Results
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Deep Voting: A Robust Approach Toward Nucleus Localization in Microscopy Images.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Nov 18, 2015
Robust and accurate nuclei localization in microscopy image can provide crucial clues for accurate computer-aid diagnosis. In this paper, we propose a convolutional neural network (CNN) based hough voting method to localize nucleus centroids with hea...
Diagnosis, Computer-Assisted Microscopy Cell Nucleus Neuroendocrine Tumors Politics Neural Networks, Computer Algorithms Reproducibility of Results Sensitivity and Specificity Humans
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Fast Cell Segmentation Using Scalable Sparse Manifold Learning and Affine Transform-approximated Active Contour.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Nov 18, 2015
Efficient and effective cell segmentation of neuroendocrine tumor (NET) in whole slide scanned images is a difficult task due to a large number of cells. The weak or misleading cell boundaries also present significant challenges. In this paper, we pr...
Cell Separation Neuroendocrine Tumors Reproducibility of Results Sensitivity and Specificity Efficiency Pancreatic Neoplasms Humans Machine Learning Algorithms
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Intraoperative monitoring of stroke volume variation versus central venous pressure in laparoscopic liver surgery: a randomized prospective comparative trial.

HPB : the official journal of the International Hepato Pancreato Biliary Association Nov 17, 2015
BACKGROUND: Central venous pressure (CVP) is used as a marker of cardiac preload to control intraoperative blood loss in open hepatectomies, while its reliability in laparoscopy is less certain. The aim of this randomized prospective trial was to eva...
Hepatectomy Proportional Hazards Models Multivariate Analysis Middle Aged Conversion to Open Surgery Central Venous Pressure Postoperative Complications Predictive Value of Tests Risk Factors Treatment Outcome Time Factors Laparoscopy Humans Aged Monitoring, Intraoperative Blood Loss, Surgical Italy Prospective Studies Male Blood Transfusion Chi-Square Distribution Stroke Volume Operative Time Female Reproducibility of Results
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