AIMC Topic: Machine Learning

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Rank-based pooling for deep convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society Jul 20, 2016
Pooling is a key mechanism in deep convolutional neural networks (CNNs) which helps to achieve translation invariance. Numerous studies, both empirically and theoretically, show that pooling consistently boosts the performance of the CNNs. The conven...
Machine Learning Neural Networks, Computer
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In Silico Calculation of Infinite Dilution Activity Coefficients of Molecular Solutes in Ionic Liquids: Critical Review of Current Methods and New Models Based on Three Machine Learning Algorithms.

Journal of chemical information and modeling Jul 20, 2016
The aim of the paper is to address all the disadvantages of currently available models for calculating infinite dilution activity coefficients (γ(∞)) of molecular solutes in ionic liquids (ILs)-a relevant property from the point of view of many appli...
Computer Simulation Support Vector Machine Molecular Conformation Ionic Liquids Solutions Linear Models Models, Molecular Neural Networks, Computer Machine Learning
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Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers.

Applied clinical informatics Jul 20, 2016
OBJECTIVE: The objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1-5.99 years) using structured and unstructured data from the electronic health record (EHR).
Child, Preschool Child Early Diagnosis Tertiary Healthcare Pediatric Obesity Infant Comorbidity Female Male Humans Machine Learning
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A computational framework for converting textual clinical diagnostic criteria into the quality data model.

Journal of biomedical informatics Jul 19, 2016
BACKGROUND: Constructing standard and computable clinical diagnostic criteria is an important but challenging research field in the clinical informatics community. The Quality Data Model (QDM) is emerging as a promising information model for standard...
Humans Machine Learning Natural Language Processing Data Accuracy Algorithms Diagnosis, Computer-Assisted
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A local Vapnik-Chervonenkis complexity.

Neural networks : the official journal of the International Neural Network Society Jul 18, 2016
We define in this work a new localized version of a Vapnik-Chervonenkis (VC) complexity, namely the Local VC-Entropy, and, building on this new complexity, we derive a new generalization bound for binary classifiers. The Local VC-Entropy-based bound ...
Machine Learning Entropy
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Artificial intelligence expert systems with neural network machine learning may assist decision-making for extractions in orthodontic treatment planning.

The journal of evidence-based dental practice Jul 18, 2016
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: New approach for the diagnosis of extractions with neural network machine learning. Seok-Ki Jung and Tae-Woo Kim. Am J Orthod Dentofacial Orthop 2016;149:127-33.
Machine Learning Decision Making Expert Systems Humans Neural Networks, Computer Artificial Intelligence
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ADMET Evaluation in Drug Discovery. 16. Predicting hERG Blockers by Combining Multiple Pharmacophores and Machine Learning Approaches.

Molecular pharmaceutics Jul 18, 2016
Blockade of human ether-à-go-go related gene (hERG) channel by compounds may lead to drug-induced QT prolongation, arrhythmia, and Torsades de Pointes (TdP), and therefore reliable prediction of hERG liability in the early stages of drug design is qu...
Machine Learning Drug Discovery Support Vector Machine Bayes Theorem Quantitative Structure-Activity Relationship Potassium Channel Blockers Cluster Analysis Models, Molecular
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Round Randomized Learning Vector Quantization for Brain Tumor Imaging.

Computational and mathematical methods in medicine Jul 18, 2016
Brain magnetic resonance imaging (MRI) classification into normal and abnormal is a critical and challenging task. Owing to that, several medical imaging classification techniques have been devised in which Learning Vector Quantization (LVQ) is among...
Nonlinear Dynamics Problem Solving Magnetic Resonance Imaging Models, Statistical Computer Simulation Machine Learning Humans Algorithms Reproducibility of Results Diagnosis, Computer-Assisted Neural Networks, Computer Brain Neoplasms Image Processing, Computer-Assisted
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Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

Drug design, development and therapy Jul 18, 2016
BACKGROUND: Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, inc...
Estrogen Receptor beta Humans Open Access Publishing Computer Simulation Drug Discovery Machine Learning Quantitative Structure-Activity Relationship Databases, Factual
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Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments.

Journal of evaluation in clinical practice Jul 15, 2016
RATIONALE, AIMS AND OBJECTIVES: Interventions with multivalued treatments are common in medical and health research; examples include comparing the efficacy of competing interventions and contrasting various doses of a drug. In recent years, there ha...
Algorithms Female Aged Humans Machine Learning Treatment Outcome Causality Regression Analysis Male Middle Aged Empirical Research Propensity Score Observation
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