AI Medical Compendium Topic

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Observational Studies as Topic

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Vitamin D status in relation to Crohn's disease: Meta-analysis of observational studies.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVES: Inconsistent findings have been published regarding vitamin D status among patients with Crohn's disease (CD) and the association with disease severity. We aimed to perform a meta-analysis evaluating serum 25-hydroxy vitamin D and 1,25 de...

Robotic versus Laparoscopic Gastrectomy for Gastric Carcinoma: a Meta-Analysis of Efficacy and Safety.

Asian Pacific journal of cancer prevention : APJCP
PURPOSE: To systematically review efficacyand safety of robotic gastrectomy (RG) compared with conventional laparoscopic gastrectomy (LG) for gastric carcinoma.

Using machine learning to assess covariate balance in matching studies.

Journal of evaluation in clinical practice
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference ...

Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

American journal of epidemiology
Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of causal effect estimation use propensity score methods or G-computation, targeted maximum likelihood esti...

Using classification tree analysis to generate propensity score weights.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alte...

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement the framework across computational environments and observational heal...

Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data.

Clinical radiology
Machine learning is now being increasingly employed in radiology to assist with tasks such as automatic lesion detection, segmentation, and characterisation. We are currently involved in an National Institute of Health Research (NIHR)-funded project,...