AIMC Topic: Data Interpretation, Statistical

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[A brief history of artificial intelligence].

Medecine sciences : M/S Nov 5, 2020
For more than a decade, we have witnessed an acceleration in the development and the adoption of artificial intelligence (AI) technologies. In medicine, it impacts clinical and fundamental research, hospital practices, medical examinations, hospital ...
Algorithms Forecasting Computer Simulation Deep Learning Humans Artificial Intelligence Software Data Analysis History, 20th Century Data Interpretation, Statistical Data Curation History, 21st Century Comprehension Knowledge History, 19th Century
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Statistical and Machine-Learning Analyses in Nutritional Genomics Studies.

Nutrients Oct 14, 2020
Nutritional compounds may have an influence on different OMICs levels, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and metagenomics. The integration of OMICs data is challenging but may provide new knowledge to explain...
Data Interpretation, Statistical Eating Data Mining Nutrition Disorders Humans Nutrigenomics Algorithms Machine Learning Nutritional Physiological Phenomena Genome-Wide Association Study Cluster Analysis
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Recommendations for Reporting Machine Learning Analyses in Clinical Research.

Circulation. Cardiovascular quality and outcomes Oct 14, 2020
Use of machine learning (ML) in clinical research is growing steadily given the increasing availability of complex clinical data sets. ML presents important advantages in terms of predictive performance and identifying undiscovered subpopulations of ...
Editorial Policies Biomedical Research Data Interpretation, Statistical Periodicals as Topic Humans Machine Learning Research Design Data Accuracy
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Comparing a novel machine learning method to the Friedewald formula and Martin-Hopkins equation for low-density lipoprotein estimation.

PloS one Sep 30, 2020
BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) is a target for cardiovascular prevention. Contemporary equations for LDL-C estimation have limited accuracy in certain scenarios (high triglycerides [TG], very low LDL-C).
Middle Aged Data Interpretation, Statistical Cholesterol, LDL Hyperlipidemias Humans Aged Triglycerides Machine Learning Cholesterol, HDL Adult Female Male
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Comparing biological and artificial vision systems: Network measures of functional connectivity.

Neuroscience letters Sep 24, 2020
Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine le...
Neurons Visual Cortex Recognition, Psychology Mice Models, Neurological Data Interpretation, Statistical Neural Networks, Computer Animals
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A non-parametric effect-size measure capturing changes in central tendency and data distribution shape.

PloS one Sep 24, 2020
MOTIVATION: Calculating the magnitude of treatment effects or of differences between two groups is a common task in quantitative science. Standard effect size measures based on differences, such as the commonly used Cohen's, fail to capture the treat...
Biostatistics Humans Artificial Intelligence Data Interpretation, Statistical Behavioral Research
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Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP Aug 1, 2020
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.
Incidence ROC Curve United States Follow-Up Studies Data Interpretation, Statistical Adult Breast Neoplasms Middle Aged Female Aged Aged, 80 and over Machine Learning Prognosis Humans Neural Networks, Computer
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Machine learning outcome regression improves doubly robust estimation of average causal effects.

Pharmacoepidemiology and drug safety Jul 27, 2020
BACKGROUND: Doubly robust estimation produces an unbiased estimator for the average treatment effect unless both propensity score (PS) and outcome models are incorrectly specified. Studies have shown that the doubly robust estimator is subject to mor...
Bias Propensity Score Computer Simulation Pharmacoepidemiology Causality Models, Statistical Humans Data Interpretation, Statistical Machine Learning
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Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

Medical image analysis Jul 21, 2020
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the crucial step in fighting COVID-19 is the ability to detect the infected p...
Predictive Value of Tests Data Interpretation, Statistical Humans Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Radiography, Thoracic Betacoronavirus Coronavirus Infections Datasets as Topic Sensitivity and Specificity Pneumonia, Viral Deep Learning Diagnosis, Differential Pandemics COVID-19 SARS-CoV-2
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Feature Selection for High-Dimensional and Imbalanced Biomedical Data Based on Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm.

Genes Jun 27, 2020
The training machine learning algorithm from an imbalanced data set is an inherently challenging task. It becomes more demanding with limited samples but with a massive number of features (high dimensionality). The high dimensional and imbalanced dat...
Humans Machine Learning Data Interpretation, Statistical Data Accuracy Animals Genomics Databases, Genetic
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