AIMC Topic: Bias

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Demographic Reporting in Publicly Available Chest Radiograph Data Sets: Opportunities for Mitigating Sex and Racial Disparities in Deep Learning Models.

Journal of the American College of Radiology : JACR Jan 1, 2022
OBJECTIVE: Data sets with demographic imbalances can introduce bias in deep learning models and potentially amplify existing health disparities. We evaluated the reporting of demographics and potential biases in publicly available chest radiograph (C...
Bias Ethnicity Female Male Deep Learning Radiography Humans
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Deep Learning for Outcome Prediction in Neurosurgery: A Systematic Review of Design, Reporting, and Reproducibility.

Neurosurgery Jan 1, 2022
Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity of data required and lack of model interpretability represent substantial barriers to the validity a...
Humans Prognosis Bias Neurosurgery Reproducibility of Results Deep Learning
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Rising to the challenge of bias in health care AI.

Nature medicine Dec 1, 2021
Standfirst: AI-based models may amplify pre-existing human bias within datasets; addressing this problem will require fundamental a realignment of the culture of software development.
Artificial Intelligence Delivery of Health Care Bias
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AIPW: An R Package for Augmented Inverse Probability-Weighted Estimation of Average Causal Effects.

American journal of epidemiology Dec 1, 2021
An increasing number of recent studies have suggested that doubly robust estimators with cross-fitting should be used when estimating causal effects with machine learning methods. However, not all existing programs that implement doubly robust estima...
Machine Learning Computer Simulation Humans Randomized Controlled Trials as Topic Data Interpretation, Statistical Causality Observational Studies as Topic Bias Software Design
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The false hope of current approaches to explainable artificial intelligence in health care.

The Lancet. Digital health Nov 1, 2021
The black-box nature of current artificial intelligence (AI) has caused some to question whether AI must be explainable to be used in high-stakes scenarios such as medicine. It has been argued that explainable AI will engender trust with the health-c...
Trust Decision Making Diagnostic Imaging Bias Delivery of Health Care Humans Communication Artificial Intelligence Health Personnel Dissent and Disputes Models, Biological Comprehension
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Risk of Bias and Error From Data Sets Used for Dermatologic Artificial Intelligence.

JAMA dermatology Nov 1, 2021
Artificial Intelligence Bias Humans
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Simply Adjusting for Schedulers' Bias in Estimated Case Durations Can Accomplish the Same Objectives of Improving Predictions as Use of Machine Learning-Reply.

JAMA surgery Nov 1, 2021
Bias Humans Machine Learning
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Simply Adjusting for Schedulers' Bias in Estimated Case Durations Can Accomplish the Same Objectives of Improving Predictions as Use of Machine Learning.

JAMA surgery Nov 1, 2021
Bias Humans Machine Learning
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Invited Commentary: Quantitative Bias Analysis Can See the Forest for the Trees.

American journal of epidemiology Sep 1, 2021
The accompanying article by Jiang et al. (Am J Epidemiol. 2021;190(9):1830-1840) extends quantitative bias analysis from the realm of statistical models to the realm of machine learning algorithms. Given the rooting of statistical models in the spiri...
Machine Learning Algorithms Humans Models, Statistical Bias
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Thirteen Questions About Using Machine Learning in Causal Research (You Won't Believe the Answer to Number 10!).

American journal of epidemiology Aug 1, 2021
Machine learning is gaining prominence in the health sciences, where much of its use has focused on data-driven prediction. However, machine learning can also be embedded within causal analyses, potentially reducing biases arising from model misspeci...
Causality Machine Learning Bias Humans Data Interpretation, Statistical Algorithms Epidemiologic Methods
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