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Bias

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Effects of medium- and long-distance running on cardiac damage markers in amateur runners: a systematic review, meta-analysis, and metaregression.

Journal of sport and health science
BACKGROUND: To finish an endurance race, athletes perform a vigorous effort that induces the release of cardiac damage markers. There are several factors that can affect the total number of these markers, so the aim of this review was to analyze the ...

Automated content analysis across six languages.

PloS one
Corpus selection bias in international relations research presents an epistemological problem: How do we know what we know? Most social science research in the field of text analytics relies on English language corpora, biasing our ability to underst...

Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis.

Nature
Most chemical experiments are planned by human scientists and therefore are subject to a variety of human cognitive biases, heuristics and social influences. These anthropogenic chemical reaction data are widely used to train machine-learning models ...

Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study.

BMC medical informatics and decision making
OBJECTIVE: Assessing risks of bias in randomized controlled trials (RCTs) is an important but laborious task when conducting systematic reviews. RobotReviewer (RR), an open-source machine learning (ML) system, semi-automates bias assessments. We cond...

A deep learning approach to estimation of subject-level bias and variance in high angular resolution diffusion imaging.

Magnetic resonance imaging
The ability to evaluate empirical diffusion MRI acquisitions for quality and to correct the resulting imaging metrics allows for improved inference and increased replicability. Previous work has shown promise for estimation of bias and variance of ge...

In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening.

Journal of chemical information and modeling
Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. ML methods such as convolutional neural networks show promising results and often outperform traditional methods such as e...