AIMC Topic: Machine Learning

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Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Effective utilization of multi-center data for autism spectrum disorder (ASD) diagnosis recently has attracted increasing attention, since a large number of subjects from multiple centers are beneficial for investigating the pathological changes of A...
Sensitivity and Specificity Humans Machine Learning Algorithms Databases, Factual Autism Spectrum Disorder Reproducibility of Results
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Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...
Placenta Pattern Recognition, Automated Reproducibility of Results Sensitivity and Specificity Ultrasonography Humans Machine Learning Algorithms Pregnancy Female
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Adversarial Similarity Network for Evaluating Image Alignment in Deep Learning based Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 26, 2018
This paper introduces an unsupervised adversarial similarity network for image registration. Unlike existing deep learning registration frameworks, our approach does not require ground-truth deformations and specific similarity metrics. We connect a ...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Reproducibility of Results Sensitivity and Specificity Humans Deep Learning Machine Learning Algorithms Brain
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Artificial Intelligence Applied to Osteoporosis: A Performance Comparison of Machine Learning Algorithms in Predicting Fragility Fractures From MRI Data.

Journal of magnetic resonance imaging : JMRI Sep 25, 2018
BACKGROUND: A current challenge in osteoporosis is identifying patients at risk of bone fracture.
Osteoporosis Female Reproducibility of Results Machine Learning Algorithms Prospective Studies Case-Control Studies ROC Curve Image Processing, Computer-Assisted Aged Cross-Sectional Studies Middle Aged Humans Body Mass Index Osteoporotic Fractures Magnetic Resonance Imaging Linear Models
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A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Sep 25, 2018
OBJECTIVE: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson's disease. This will assist in consolidating current knowledge and...
Humans Machine Learning Parkinson Disease Deep Brain Stimulation Microelectrodes Electrodes, Implanted
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Deep learning with convolutional neural network for objective skill evaluation in robot-assisted surgery.

International journal of computer assisted radiology and surgery Sep 25, 2018
PURPOSE: With the advent of robot-assisted surgery, the role of data-driven approaches to integrate statistics and machine learning is growing rapidly with prominent interests in objective surgical skill assessment. However, most existing work requir...
Biomechanical Phenomena Deep Learning Clinical Competence Gestures Robotics Humans Neural Networks, Computer Machine Learning
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Predicting of anaphylaxis in big data EMR by exploring machine learning approaches.

Journal of biomedical informatics Sep 25, 2018
Anaphylaxis is a life-threatening allergic reaction that occurs suddenly after contact with an allergen. Epidemiological studies about anaphylaxis are very important in planning and evaluating new strategies that prevent this reaction, but also in pr...
Medical Informatics Linear Models Anaphylaxis Electronic Health Records Language Cluster Analysis Big Data Neural Networks, Computer Humans Decision Making Machine Learning Regression Analysis Algorithms
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Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Machine Learning for Molecular Recognition of Myocardial Infarction.

Analytical chemistry Sep 25, 2018
Lipid profile changes in heart muscle have been previously linked to cardiac ischemia and myocardial infarction, but the spatial distribution of lipids and metabolites in ischemic heart remains to be fully investigated. We performed desorption electr...
Machine Learning Female Myocardial Infarction Spectrometry, Mass, Electrospray Ionization Molecular Imaging Fatty Acids, Unsaturated Animals Mice Molecular Structure
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Learning zero-cost portfolio selection with pattern matching.

PloS one Sep 25, 2018
We replicate and extend the adversarial expert based learning approach of Györfi et al to the situation of zero-cost portfolio selection implemented with a quadratic approximation derived from the mutual fund separation theorems. The algorithm is app...
Machine Learning Algorithms Models, Economic Cluster Analysis South Africa New York City
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Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method.

mAbs Sep 25, 2018
Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious diseases. Similar to any protein molecule, mAbs are susceptible to chemical modifications during the ...
Complementarity Determining Regions Computer Simulation Kinetics Protein Binding Antigens Antineoplastic Agents, Immunological Methionine Antibodies, Monoclonal Oxidation-Reduction Humans Machine Learning Treatment Outcome
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