AIMC Topic: Data Interpretation, Statistical
Clear Filters Showing 191 to 200 of 233 articles
Estimating Treatment Effect Heterogeneity in Psychiatry: A Review and Tutorial With Causal Forests.
International journal of methods in psychiatric research
Jun 1, 2025
BACKGROUND: Flexible machine learning tools are increasingly used to estimate heterogeneous treatment effects.
Assessing the accuracy and efficiency of Chat GPT-4 Omni (GPT-4o) in biomedical statistics: Comparative study with traditional tools.
Saudi medical journal
Dec 1, 2024
OBJECTIVES: To assess the accuracy of ChatGPT-4 Omni (GPT-4o) in biomedical statistics. The recent novel inauguration of Artificial Intelligence ChatGPT-Omni (GPT-4o), has emerged with the potential to analyze sophisticated and extensive data sets, c...
Addressing the Generalizability of AI in Radiology Using a Novel Data Augmentation Framework with Synthetic Patient Image Data: Proof-of-Concept and External Validation for Classification Tasks in Multiple Sclerosis.
Radiology. Artificial intelligence
Nov 1, 2024
Artificial intelligence (AI) models often face performance drops after deployment to external datasets. This study evaluated the potential of a novel data augmentation framework based on generative adversarial networks (GANs) that creates synthetic p...
Considering Biased Data as Informative Artifacts in AI-Assisted Health Care.
The New England journal of medicine
Aug 31, 2023
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...
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...
Artificial intelligence-cogito, ergo sum.
Cancer metastasis reviews
Jun 1, 2021
Data Analysis for Antibody Arrays.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2021
When obtaining high-throughput data from antibody arrays, researchers have to face a couple of questions: How and by what means can they get reasonable results significant to their research from these data? Similar to a gene microarray, the classical...
Interpretation of artificial intelligence studies for the ophthalmologist.
Current opinion in ophthalmology
Sep 1, 2020
PURPOSE OF REVIEW: The use of artificial intelligence (AI) in ophthalmology has increased dramatically. However, interpretation of these studies can be a daunting prospect for the ophthalmologist without a background in computer or data science. This...
Machine Learning Within Studies of Early-Life Environmental Exposures and Child Health: Review of the Current Literature and Discussion of Next Steps.
Current environmental health reports
Sep 1, 2020
PURPOSE OF REVIEW: The goal of this article is to review the use of machine learning (ML) within studies of environmental exposures and children's health, identify common themes across studies, and provide recommendations to advance their use in rese...
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