AIMC Topic: Case-Control Studies
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Automated detection of altered mental status in emergency department clinical notes: a deep learning approach.
BMC medical informatics and decision making
Aug 19, 2019
BACKGROUND: Machine learning has been used extensively in clinical text classification tasks. Deep learning approaches using word embeddings have been recently gaining momentum in biomedical applications. In an effort to automate the identification o...
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data.
EBioMedicine
Aug 13, 2019
BACKGROUND: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information.
Ankle torque steadiness and gait speed after a single session of robot therapy in individuals with chronic hemiparesis: a pilot study.
Topics in stroke rehabilitation
Aug 1, 2019
Anklebot therapy has proven to be effective in improving hemiparetic gait. However, neither ankle torque steadiness nor the relationship between changes in force control and functional tasks after therapy with Anklebot were described. To assess whet...
An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction.
Lancet (London, England)
Aug 1, 2019
BACKGROUND: Atrial fibrillation is frequently asymptomatic and thus underdetected but is associated with stroke, heart failure, and death. Existing screening methods require prolonged monitoring and are limited by cost and low yield. We aimed to deve...
Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis.
The Journal of asthma : official journal of the Association for the Care of Asthma
Jul 26, 2019
To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and allied-conditions (COPDAC) using a multi domain analysis of socio-ecological, clinical, and demographic domains. This is a retrospective case-risk-co...
Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.
Journal of dental research
Jul 24, 2019
This study's objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial intelligence to test shape analysis features in a neural network (NN) to stage condylar morphology in te...
Denoising and artefact removal for transthoracic echocardiographic imaging in congenital heart disease: utility of diagnosis specific deep learning algorithms.
The international journal of cardiovascular imaging
Jul 19, 2019
Deep learning (DL) algorithms are increasingly used in cardiac imaging. We aimed to investigate the utility of DL algorithms in de-noising transthoracic echocardiographic images and removing acoustic shadowing artefacts specifically in patients with ...
Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.
Statistics in medicine
Jul 15, 2019
Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection me...
Performance of a Natural Language Processing Method to Extract Stone Composition From the Electronic Health Record.
Urology
Jul 13, 2019
OBJECTIVES: To demonstrate the utility of a natural language processing (NLP) algorithm for mining kidney stone composition in a large-scale electronic health records (EHR) repository.
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.
World neurosurgery
Jul 9, 2019
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.
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