AIMC Topic: Observational Studies as Topic

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Long-term mesh erosion rate following abdominal robotic reconstructive pelvic floor surgery: a prospective study and overview of the literature.

International urogynecology journal Jun 20, 2019
INTRODUCTION AND HYPOTHESIS: The use of synthetic mesh in transvaginal pelvic floor surgery has been subject to debate internationally. Although mesh erosion appears to be less associated with an abdominal approach, the long-term outcome has not been...
Pelvic Organ Prolapse Surgical Mesh Treatment Outcome Observational Studies as Topic Robotics Humans Robotic Surgical Procedures Retrospective Studies Plastic Surgery Procedures Prospective Studies Pelvic Floor Female Laparoscopy
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Machine learning methods for developing precision treatment rules with observational data.

Behaviour research and therapy May 28, 2019
Clinical trials have identified a variety of predictor variables for use in precision treatment protocols, ranging from clinical biomarkers and symptom profiles to self-report measures of various sorts. Although such variables are informative collect...
Observational Studies as Topic Information Storage and Retrieval Clinical Decision Rules Suicide, Attempted Suicide Prevention Decision Support Systems, Clinical Databases, Factual Precision Medicine Humans Machine Learning
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A comparison of machine learning algorithms and covariate balance measures for propensity score matching and weighting.

Biometrical journal. Biometrische Zeitschrift May 14, 2019
Propensity score matching (PSM) and propensity score weighting (PSW) are popular tools to estimate causal effects in observational studies. We address two open issues: how to estimate propensity scores and assess covariate balance. Using simulations,...
Humans Cesarean Section Observational Studies as Topic Labor, Induced Multivariate Analysis Machine Learning Pregnancy Female Propensity Score Monte Carlo Method Biometry
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Estimating the Population Average Treatment Effect in Observational Studies with Choice-Based Sampling.

The international journal of biostatistics Apr 16, 2019
We consider causal inference in observational studies with choice-based sampling, in which subject enrollment is stratified on treatment choice. Choice-based sampling has been considered mainly in the econometrics literature, but it can be useful for...
Sample Size Data Interpretation, Statistical Likelihood Functions Machine Learning Computer Simulation Observational Studies as Topic Models, Statistical Humans
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Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data.

Clinical radiology Feb 23, 2019
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,...
Multicenter Studies as Topic Whole Body Imaging Humans Machine Learning Magnetic Resonance Imaging Observational Studies as Topic Algorithms Neoplasms
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Using classification tree analysis to generate propensity score weights.

Journal of evaluation in clinical practice Mar 28, 2017
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...
Humans Monte Carlo Method Observational Studies as Topic Data Interpretation, Statistical Machine Learning Models, Statistical Computer Simulation Propensity Score Logistic Models
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Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

American journal of epidemiology Dec 9, 2016
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...
Data Interpretation, Statistical Bias Propensity Score Epidemiologic Research Design Likelihood Functions Confounding Factors, Epidemiologic Exercise Depression Causality Observational Studies as Topic Humans Machine Learning Computer Simulation
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Using machine learning to assess covariate balance in matching studies.

Journal of evaluation in clinical practice Mar 23, 2016
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 ...
Research Design Observational Studies as Topic Retrospective Studies Male Humans Discriminant Analysis Patient-Centered Care Female Middle Aged Machine Learning Propensity Score Adult Pilot Projects Algorithms
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Vitamin D status in relation to Crohn's disease: Meta-analysis of observational studies.

Nutrition (Burbank, Los Angeles County, Calif.) Dec 22, 2015
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...
Vitamin D Deficiency Prevalence Sunlight Observational Studies as Topic Nutritional Status Severity of Illness Index Crohn Disease Humans 25-Hydroxyvitamin D 2 Evidence-Based Medicine Child Adult Global Health
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External Validation of an Algorithm to Guide Opioid Administration at the End of Surgery-Protocol for an Observational Cohort Study of the OPIAID Algorithm.

Acta anaesthesiologica Scandinavica Jul 1, 2025
BACKGROUND: Despite advances in pain management, inadequate pain relief and opioid-related adverse events remain common challenges in perioperative care, often contributing to prolonged recovery and reduced quality of life. The perioperative opioid a...
Machine Learning Algorithms Prospective Studies Reproducibility of Results Humans Pain, Postoperative Analgesics, Opioid Adult Pain Management Perioperative Care Cohort Studies Observational Studies as Topic
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