AIMC Topic: Bias
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Systematic auditing is essential to debiasing machine learning in biology.
Communications biology
Feb 10, 2021
Biases in data used to train machine learning (ML) models can inflate their prediction performance and confound our understanding of how and what they learn. Although biases are common in biological data, systematic auditing of ML models to identify ...
Agreement in Risk of Bias Assessment Between RobotReviewer and Human Reviewers: An Evaluation Study on Randomised Controlled Trials in Nursing-Related Cochrane Reviews.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Feb 8, 2021
PURPOSE: RobotReviewer is a machine learning system for semi-automated assistance in risk of bias assessment. The tools's performance in randomized controlled trials (RCTs) in the field of nursing remains unknown. We aimed therefore to evaluate the a...
For a critical appraisal of artificial intelligence in healthcare: The problem of bias in mHealth.
Journal of evaluation in clinical practice
Dec 23, 2020
RATIONALE, AIMS AND OBJECTIVES: Artificial intelligence and big data are more and more used in medicine, either in prevention, diagnosis or treatment, and are clearly modifying the way medicine is thought and practiced. Some authors argue that the us...
Artificial Intelligence in mental health and the biases of language based models.
PloS one
Dec 17, 2020
BACKGROUND: The rapid integration of Artificial Intelligence (AI) into the healthcare field has occurred with little communication between computer scientists and doctors. The impact of AI on health outcomes and inequalities calls for health professi...
Addressing bias: artificial intelligence in cardiovascular medicine.
The Lancet. Digital health
Nov 23, 2020
Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.
BMJ open
Nov 11, 2020
INTRODUCTION: Studies addressing the development and/or validation of diagnostic and prognostic prediction models are abundant in most clinical domains. Systematic reviews have shown that the methodological and reporting quality of prediction model s...
Electromechanical-assisted training for walking after stroke.
The Cochrane database of systematic reviews
Oct 22, 2020
BACKGROUND: Electromechanical- and robot-assisted gait-training devices are used in rehabilitation and might help to improve walking after stroke. This is an update of a Cochrane Review first published in 2007 and previously updated in 2017.
The automation of bias in medical Artificial Intelligence (AI): Decoding the past to create a better future.
Artificial intelligence in medicine
Oct 6, 2020
Medicine is at a disciplinary crossroads. With the rapid integration of Artificial Intelligence (AI) into the healthcare field the future care of our patients will depend on the decisions we make now. Demographic healthcare inequalities continue to p...
Bias and ethical considerations in machine learning and the automation of perioperative risk assessment.
British journal of anaesthesia
Aug 21, 2020
Evolution and impact of bias in human and machine learning algorithm interaction.
PloS one
Aug 13, 2020
Traditionally, machine learning algorithms relied on reliable labels from experts to build predictions. More recently however, algorithms have been receiving data from the general population in the form of labeling, annotations, etc. The result is th...
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