AI Medical Compendium Topic:
Models, Statistical

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WEVar: a novel statistical learning framework for predicting noncoding regulatory variants.

Briefings in bioinformatics
Understanding the functional consequence of noncoding variants is of great interest. Though genome-wide association studies or quantitative trait locus analyses have identified variants associated with traits or molecular phenotypes, most of them are...

Exploration of Machine Learning and Statistical Techniques in Development of a Low-Cost Screening Method Featuring the Global Diet Quality Score for Detecting Prediabetes in Rural India.

The Journal of nutrition
BACKGROUND: The prevalence of type 2 diabetes has increased substantially in India over the past 3 decades. Undiagnosed diabetes presents a public health challenge, especially in rural areas, where access to laboratory testing for diagnosis may not b...

Invited Commentary: Quantitative Bias Analysis Can See the Forest for the Trees.

American journal of epidemiology
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...

Revisiting genome-wide association studies from statistical modelling to machine learning.

Briefings in bioinformatics
Over the last decade, genome-wide association studies (GWAS) have discovered thousands of genetic variants underlying complex human diseases and agriculturally important traits. These findings have been utilized to dissect the biological basis of dis...

Development and validation of a machine learning model predicting illness trajectory and hospital utilization of COVID-19 patients: A nationwide study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The spread of coronavirus disease 2019 (COVID-19) has led to severe strain on hospital capacity in many countries. We aim to develop a model helping planners assess expected COVID-19 hospital resource utilization based on individual patien...

Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Cause of death is used as an important outcome of clinical research; however, access to cause-of-death data is limited. This study aimed to develop and validate a machine-learning model that predicts the cause of death from the patient's l...

Designing COVID-19 mortality predictions to advance clinical outcomes: Evidence from the Department of Veterans Affairs.

BMJ health & care informatics
Using administrative data on all Veterans who enter Department of Veterans Affairs (VA) medical centres throughout the USA, this paper uses artificial intelligence (AI) to predict mortality rates for patients with COVID-19 between March and August 20...