AIMC Topic: Data Interpretation, Statistical

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Machine learning in the estimation of causal effects: targeted minimum loss-based estimation and double/debiased machine learning.

Biostatistics (Oxford, England) Apr 1, 2020
In recent decades, the fields of statistical and machine learning have seen a revolution in the development of data-adaptive regression methods that have optimal performance under flexible, sometimes minimal, assumptions on the true regression functi...
Causality Models, Statistical Data Interpretation, Statistical Biostatistics Humans Machine Learning
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Statistical and Machine Learning Methods for eQTL Analysis.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
An immense amount of observable diversity exists for all traits and across global populations. In the post-genomic era, equipped with efficient sequencing capabilities and better genotyping methods, we are now able to more fully appreciate how regula...
Data Interpretation, Statistical Gene Expression Quantitative Trait Loci Machine Learning Genome-Wide Association Study Computational Biology Chromosome Mapping Humans
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The role of artificial intelligence and machine learning in predicting orthopaedic outcomes.

The bone & joint journal Dec 1, 2019
This annotation briefly reviews the history of artificial intelligence and machine learning in health care and orthopaedics, and considers the role it will have in the future, particularly with reference to statistical analyses involving large datase...
United States Data Interpretation, Statistical United Kingdom History, 20th Century Clinical Decision Rules Machine Learning Humans Orthopedic Procedures Forecasting Artificial Intelligence Prognosis
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A data-driven update of arterial perfusion territories.

Nature reviews. Neurology Nov 1, 2019
Machine Learning Data Interpretation, Statistical Stroke Magnetic Resonance Angiography Humans Cerebrovascular Circulation
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Skeletal bone age assessments for young children based on regression convolutional neural networks.

Mathematical biosciences and engineering : MBE Jul 12, 2019
Pediatricians and pediatric endocrinologists utilize Bone Age Assessment (BAA) for in-vestigations pertaining to genetic disorders, hormonal complications and abnormalities in the skeletal system maturity of children. Conventional methods dating back...
Pattern Recognition, Automated X-Rays Age Determination by Skeleton Carpal Bones Regression Analysis Infant, Newborn Data Interpretation, Statistical Reproducibility of Results Observer Variation Young Adult Child, Preschool Child Neural Networks, Computer Humans Image Processing, Computer-Assisted Male China Algorithms Infant Adolescent Female
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Extremely Reduced Data Sets Indicate Optimal Stimulation Parameters for Classification in Brain-Computer Interfaces.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The time between the onset of subsequent auditory or visual stimuli - also known as stimulus onset asynchrony (SOA) - determines many of the event-related potential characteristics of the resulting evoked brain signals. Specifically, the SOA value in...
Machine Learning Brain Decision Making Data Interpretation, Statistical Electroencephalography Brain-Computer Interfaces Humans Photic Stimulation Evoked Potentials
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Can Hyperparameter Tuning Improve the Performance of a Super Learner?: A Case Study.

Epidemiology (Cambridge, Mass.) Jul 1, 2019
BACKGROUND: Super learning is an ensemble machine learning approach used increasingly as an alternative to classical prediction techniques. When implementing super learning, however, not tuning the hyperparameters of the algorithms in it may adversel...
Logistic Models Data Interpretation, Statistical Practice Patterns, Physicians' Algorithms Primary Health Care Canada Antidepressive Agents Off-Label Use Humans Machine Learning
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Signals Among Signals: Prioritizing Nongenetic Associations in Massive Data Sets.

American journal of epidemiology May 1, 2019
Massive data sets are often regarded as a panacea to the underpowered studies of the past. At the same time, it is becoming clear that in many of these data sets in which thousands of variables are measured across hundreds of thousands or millions of...
Biostatistics Epidemiologic Research Design Models, Statistical Humans Data Interpretation, Statistical Machine Learning Confounding Factors, Epidemiologic Big Data
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Common Audiological Functional Parameters (CAFPAs): statistical and compact representation of rehabilitative audiological classification based on expert knowledge.

International journal of audiology Apr 1, 2019
OBJECTIVE: As a step towards objectifying audiological rehabilitation and providing comparability between different test batteries and clinics, the Common Audiological Functional Parameters (CAFPAs) were introduced as a common and abstract representa...
Data Interpretation, Statistical Humans Probability Expert Systems Hearing Tests Hearing Disorders Machine Learning Audiology Reproducibility of Results Correction of Hearing Impairment Predictive Value of Tests
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A sparse deep learning model for privacy attack on remote sensing images.

Mathematical biosciences and engineering : MBE Feb 20, 2019
Deep learning tools have been a new way for privacy attacks on remote sensing images. However, since labeled data of privacy objects in remote sensing images are less, the samples for training are commonly small. Besides, traditional deep neural netw...
Deep Learning Computer Simulation Neural Networks, Computer Remote Sensing Technology Image Processing, Computer-Assisted Software Reproducibility of Results Privacy Data Interpretation, Statistical Algorithms Geographic Information Systems
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