AIMC Topic: Data Interpretation, Statistical

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A novel missing data imputation approach based on clinical conditional Generative Adversarial Networks applied to EHR datasets.

Computers in biology and medicine Jun 22, 2023
The missing data mechanism is a relevant problem in Machine Learning (ML) and biomedical informatics communities. Real-world Electronic Health Record (EHR) datasets comprise several missing values, thus revealing a high level of spatiotemporal sparsi...
Machine Learning Electronic Health Records Data Interpretation, Statistical Humans
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Interpretable machine learning for psychological research: Opportunities and pitfalls.

Psychological methods May 25, 2023
In recent years, machine learning methods have become increasingly popular prediction methods in psychology. At the same time, psychological researchers are typically not only interested in making predictions about the dependent variable, but also in...
Humans Neural Networks, Computer Machine Learning Data Interpretation, Statistical Psychology
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An introduction to causal inference for pharmacometricians.

CPT: pharmacometrics & systems pharmacology Dec 8, 2022
As formal causal inference begins to play a greater role in disciplines that intersect with pharmacometrics, such as biostatistics, epidemiology, and artificial intelligence/machine learning, pharmacometricians may increasingly benefit from a basic f...
Biometry Confounding Factors, Epidemiologic Humans Artificial Intelligence Causality Data Interpretation, Statistical
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Evaluation of machine learning methods for covariate data imputation in pharmacometrics.

CPT: pharmacometrics & systems pharmacology Nov 8, 2022
Missing data create challenges in clinical research because they lead to loss of statistical power and potentially to biased results. Missing covariate data must be handled with suitable approaches to prepare datasets for pharmacometric analyses, suc...
Data Interpretation, Statistical Bias Humans Machine Learning Computer Simulation
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Mediation analysis using Bayesian tree ensembles.

Psychological methods Jul 4, 2022
We present a general framework for causal mediation analysis using nonparametric Bayesian methods in the potential outcomes framework. Our model, which we refer to as the Bayesian causal mediation forests model, combines recent advances in Bayesian m...
Decision Trees Data Interpretation, Statistical Bayes Theorem Humans Machine Learning Models, Statistical Psychology Mediation Analysis
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A Novel Reformed Reduced Kernel Extreme Learning Machine with RELIEF-F for Classification.

Computational intelligence and neuroscience Mar 24, 2022
With the exponential growth of the Internet population, scientists and researchers face the large-scale data for processing. However, the traditional algorithms, due to their complex computation, are not suitable for the large-scale data, although th...
Machine Learning Algorithms Big Data Data Interpretation, Statistical Electronic Data Processing Humans
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Missing data imputation in clinical trials using recurrent neural network facilitated by clustering and oversampling.

Biometrical journal. Biometrische Zeitschrift Mar 10, 2022
In clinical practice, the composition of missing data may be complex, for example, a mixture of missing at random (MAR) and missing not at random (MNAR) assumptions. Many methods under the assumption of MAR are available. Under the assumption of MNAR...
Data Interpretation, Statistical Bias Likelihood Functions Neural Networks, Computer Cluster Analysis Humans
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A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.

PLoS computational biology Dec 3, 2021
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...
Whales Cetacea Software Design Echolocation Computational Biology Databases, Factual Cluster Analysis Machine Learning Animals Algorithms Unsupervised Machine Learning Deep Learning Data Interpretation, Statistical Acoustics California
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A Simulation Study to Compare the Predictive Performance of Survival Neural Networks with Cox Models for Clinical Trial Data.

Computational and mathematical methods in medicine Nov 28, 2021
BACKGROUND: Studies focusing on prediction models are widespread in medicine. There is a trend in applying machine learning (ML) by medical researchers and clinicians. Over the years, multiple ML algorithms have been adapted to censored data. However...
Data Interpretation, Statistical Clinical Trials as Topic Prognosis Machine Learning Proportional Hazards Models Male Female Algorithms Clinical Trials, Phase III as Topic Computational Biology Bone Neoplasms Computer Simulation Humans Osteosarcoma Randomized Controlled Trials as Topic Neural Networks, Computer
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A weighted patient network-based framework for predicting chronic diseases using graph neural networks.

Scientific reports Nov 19, 2021
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...
Machine Learning Reproducibility of Results Translational Research, Biomedical Cardiovascular Diseases Software Programming Languages Databases, Factual Chronic Disease Pulmonary Disease, Chronic Obstructive Humans Algorithms Risk Female Data Interpretation, Statistical Male Neural Networks, Computer
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