AIMC Topic: Probability

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Understanding and diagnosing the potential for bias when using machine learning methods with doubly robust causal estimators.

Statistical methods in medical research May 2, 2018
Data-adaptive methods have been proposed to estimate nuisance parameters when using doubly robust semiparametric methods for estimating marginal causal effects. However, in the presence of near practical positivity violations, these methods can produ...
Models, Statistical Bias Probability Propensity Score Humans Machine Learning Causality
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Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
Pattern Recognition, Automated False Positive Reactions X-Rays Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Carcinoma Probability Medical Errors Databases, Factual Reproducibility of Results Sensitivity and Specificity Humans Neural Networks, Computer Lung Algorithms Image Processing, Computer-Assisted Lung Neoplasms Solitary Pulmonary Nodule
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Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology Mar 14, 2018
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....
Female Reproducibility of Results Aged Male Humans Machine Learning Algorithms Follow-Up Studies Regression Analysis Area Under Curve Heart Middle Aged ROC Curve Support Vector Machine Death, Sudden, Cardiac Probability Risk Tomography, Emission-Computed, Single-Photon
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Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

Computer methods and programs in biomedicine Jan 31, 2018
BACKGROUND AND OBJECTIVE: Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (...
Reproducibility of Results Breast Neoplasms Diagnosis, Computer-Assisted Mammography Humans Neural Networks, Computer Probability Machine Learning Radiology Information Systems Female
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Functional Categorization of Disease Genes Based on Spectral Graph Theory and Integrated Biological Knowledge.

Interdisciplinary sciences, computational life sciences Jan 30, 2018
Interaction of multiple genetic variants is a major challenge in the development of effective treatment strategies for complex disorders. Identifying the most promising genes enhances the understanding of the underlying mechanisms of the disease, whi...
Phenotype Autism Spectrum Disorder Gene Expression Profiling Genomics Computational Biology Cluster Analysis Knowledge Bases Humans Algorithms Probability Genome, Human Oligonucleotide Array Sequence Analysis Computer Graphics
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Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Proceedings of the National Academy of Sciences of the United States of America Jan 22, 2018
Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to ca...
Genetic Predisposition to Disease Polymorphism, Single Nucleotide Humans Probability Machine Learning Genome, Human Life Style Neoplasms
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Fully automatic cervical vertebrae segmentation framework for X-ray images.

Computer methods and programs in biomedicine Jan 12, 2018
The cervical spine is a highly flexible anatomy and therefore vulnerable to injuries. Unfortunately, a large number of injuries in lateral cervical X-ray images remain undiagnosed due to human errors. Computer-aided injury detection has the potential...
Diagnostic Errors Humans Probability Radiography Neural Networks, Computer Image Interpretation, Computer-Assisted Cervical Vertebrae Algorithms Automation
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Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society Jan 12, 2018
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...
Heart Rate Probability Action Potentials Unsupervised Machine Learning Neurons Algorithms Wearable Electronic Devices Electrocardiography Humans Neuronal Plasticity
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A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning.

PLoS computational biology Jan 4, 2018
Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and a...
Probability Markov Chains Electrophysiology Nerve Net Reinforcement, Psychology Frontal Lobe Spatial Learning Magnetic Resonance Imaging Models, Neurological Decision Making Neurons Animals Prefrontal Cortex Cognition Humans Neural Networks, Computer Learning
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Divisive hierarchical maximum likelihood clustering.

BMC bioinformatics Dec 28, 2017
BACKGROUND: Biological data comprises various topologies or a mixture of forms, which makes its analysis extremely complicated. With this data increasing in a daily basis, the design and development of efficient and accurate statistical methods has b...
Probability Humans Algorithms Cluster Analysis
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