AIMC Topic: Bias
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Tackling bias in AI health datasets through the STANDING Together initiative.
Nature medicine
Nov 1, 2022
Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.
Journal of the American Medical Informatics Association : JAMIA
Jun 14, 2022
OBJECTIVE: Artificial intelligence (AI) models may propagate harmful biases in performance and hence negatively affect the underserved. We aimed to assess the degree to which data quality of electronic health records (EHRs) affected by inequities rel...
Preprocessing to Address Bias in Healthcare Data.
Studies in health technology and informatics
May 25, 2022
Multimorbidity, having a diagnosis of two or more chronic conditions, increases as people age. It is a predictor used in clinical decision-making, but underdiagnosis in underserved populations produces bias in the data that support algorithms used in...
Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.
BMJ health & care informatics
Apr 1, 2022
OBJECTIVES: The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require...
Global disparity bias in ophthalmology artificial intelligence applications.
BMJ health & care informatics
Apr 1, 2022
Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic Review.
Journal of Crohn's & colitis
Mar 14, 2022
BACKGROUND AND AIMS: There is increasing interest in machine learning-based prediction models in inflammatory bowel diseases [IBD]. We synthesised and critically appraised studies comparing machine learning vs traditional statistical models, using ro...
SuperMICE: An Ensemble Machine Learning Approach to Multiple Imputation by Chained Equations.
American journal of epidemiology
Feb 19, 2022
Researchers often face the problem of how to address missing data. Multiple imputation is a popular approach, with multiple imputation by chained equations (MICE) being among the most common and flexible methods for execution. MICE iteratively fits a...
Applications of artificial intelligence (AI) in ovarian cancer, pancreatic cancer, and image biomarker discovery.
Cancer biomarkers : section A of Disease markers
Jan 1, 2022
BACKGROUND: Artificial intelligence (AI), including machine learning (ML) and deep learning, has the potential to revolutionize biomedical research. Defined as the ability to "mimic" human intelligence by machines executing trained algorithms, AI met...
GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks.
Journal of computational biology : a journal of computational molecular cell biology
Jan 1, 2022
We propose GRNUlar, a novel deep learning framework for supervised learning of gene regulatory networks (GRNs) from single-cell RNA-Sequencing (scRNA-Seq) data. Our framework incorporates two intertwined models. First, we leverage the expressive abil...
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