AIMC Topic: Cross-Sectional Studies

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EMG Muscle Activation Pattern of Four Lower Extremity Muscles during Stair Climbing, Motor Imagery, and Robot-Assisted Stepping: A Cross-Sectional Study in Healthy Individuals.

BioMed research international
BACKGROUND: Stair climbing can be a challenging part of daily life and a limiting factor for social participation, in particular for patients after stroke. In order to promote motor relearning of stair climbing, different therapeutical measures can b...

Applications of machine learning in addiction studies: A systematic review.

Psychiatry research
This study aims to provide a systematic review of the applications of machine learning methods in addiction research. In this study, multiple searches on MEDLINE, Embase and the Cochrane Database of Systematic Reviews were performed. 23 full-text art...

Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.

The Journal of foot and ankle surgery : official publication of the American College of Foot and Ankle Surgeons
Ankle fractures are common orthopedic injuries with favorable outcomes when managed with open reduction and internal fixation (ORIF). Several patient-related risk factors may contribute to poor short-term outcomes, and machine learning may be a valua...

Modelling PTSD diagnosis using sleep, memory, and adrenergic metabolites: An exploratory machine-learning study.

Human psychopharmacology
OBJECTIVE: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This study evaluated whether these combined features may accurately delineate pathophysiological changes ...

SALMANTICOR study. Rationale and design of a population-based study to identify structural heart disease abnormalities: a spatial and machine learning analysis.

BMJ open
INTRODUCTION: This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to...

Natural language processing to identify ureteric stones in radiology reports.

Journal of medical imaging and radiation oncology
INTRODUCTION: Natural language processing (NLP) is an emerging tool which has the ability to automate data extraction from large volumes of unstructured text. One of the main described uses of NLP in radiology is cohort building for epidemiological s...

Circulating Levels of Soluble Klotho and Fibroblast Growth Factor 23 in Diabetic Patients and Its Association with Early Nephropathy.

Archives of medical research
INTRODUCTION: Diabetic nephropathy is a leading cause of chronic kidney disease (CKD). In diabetes, changes in serum levels of both soluble alpha Klotho (sKL) and fibroblast growth factor 23 (FGF-23) have been associated with CKD progression.

A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.

American journal of ophthalmology
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...