AIMC Topic: Observational Studies as Topic

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Deep Learning Predicts Total Knee Replacement from Magnetic Resonance Images.

Scientific reports Apr 14, 2020
Knee Osteoarthritis (OA) is a common musculoskeletal disorder in the United States. When diagnosed at early stages, lifestyle interventions such as exercise and weight loss can slow OA progression, but at later stages, only an invasive option is avai...
Middle Aged Case-Control Studies Deep Learning United States Female Humans Aged Male Prospective Studies Knee Joint Arthroplasty, Replacement, Knee Datasets as Topic Osteoarthritis, Knee Treatment Outcome Magnetic Resonance Imaging Observational Studies as Topic
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Exploring healthcare professionals' understanding and experiences of artificial intelligence technology use in the delivery of healthcare: An integrative review.

Health informatics journal Sep 30, 2019
BACKGROUND: The integration of artificial intelligence (AI) into our digital healthcare system is seen as a significant strategy to contain Australia's rising healthcare costs, support clinical decision making, manage chronic disease burden and suppo...
Health Personnel Delivery of Health Care Technology Humans Observational Studies as Topic Australia Artificial Intelligence
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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...
Humans Treatment Outcome Observational Studies as Topic Robotics Plastic Surgery Procedures Prospective Studies Retrospective Studies Female Laparoscopy Pelvic Organ Prolapse Robotic Surgical Procedures Surgical Mesh Pelvic Floor
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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...
Information Storage and Retrieval Clinical Decision Rules Humans Machine Learning Suicide Prevention Decision Support Systems, Clinical Observational Studies as Topic Databases, Factual Precision Medicine Suicide, Attempted
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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,...
Propensity Score Monte Carlo Method Biometry Observational Studies as Topic Labor, Induced Multivariate Analysis Humans Female Cesarean Section Machine Learning Pregnancy
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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...
Observational Studies as Topic Humans Data Interpretation, Statistical Machine Learning Models, Statistical Likelihood Functions Computer Simulation Sample Size
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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,...
Whole Body Imaging Algorithms Humans Magnetic Resonance Imaging Neoplasms Machine Learning Observational Studies as Topic Multicenter Studies as Topic
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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...
Data Interpretation, Statistical Propensity Score Monte Carlo Method Logistic Models Observational Studies as Topic Models, Statistical Humans Machine Learning Computer Simulation
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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...
Computer Simulation Exercise Depression Causality Humans Machine Learning Propensity Score Observational Studies as Topic Confounding Factors, Epidemiologic Likelihood Functions Data Interpretation, Statistical Epidemiologic Research Design Bias
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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 ...
Adult Male Middle Aged Patient-Centered Care Discriminant Analysis Propensity Score Pilot Projects Observational Studies as Topic Humans Machine Learning Algorithms Research Design Retrospective Studies Female
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