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Case-Control Studies

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A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...

Effect of Health and Training on Ultrasensitive Cardiac Troponin in Marathon Runners.

The journal of applied laboratory medicine
PURPOSE: Cardiac troponin (cTn) is the gold standard biomarker for assessing cardiac damage. Previous studies have demonstrated increases in plasma cTn because of extreme exercise, including marathon running. We developed an easy-to-use, ultrasensiti...

Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning.

Scientific reports
We present a robust deep learning framework for the automatic localisation of cone photoreceptor cells in Adaptive Optics Scanning Light Ophthalmoscope (AOSLO) split-detection images. Monitoring cone photoreceptors with AOSLO imaging grants an excell...

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
OBJECTIVE: The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifie...

Assessing Breast Cancer Risk with an Artificial Neural Network.

Asian Pacific journal of cancer prevention : APJCP
Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to esta...

Hierarchical combinatorial deep learning architecture for pancreas segmentation of medical computed tomography cancer images.

BMC systems biology
BACKGROUND: Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abd...

Assessing patient risk of central line-associated bacteremia via machine learning.

American journal of infection control
BACKGROUND: Central line-associated bloodstream infections (CLABSIs) contribute to increased morbidity, length of hospital stay, and cost. Despite progress in understanding the risk factors, there remains a need to accurately predict the risk of CLAB...

Feasibility of robot-based perturbed-balance training during treadmill walking in a high-functioning chronic stroke subject: a case-control study.

Journal of neuroengineering and rehabilitation
BACKGROUND: For stroke survivors, balance deficits that persist after the completion of the rehabilitation process lead to a significant risk of falls. We have recently developed a balance-assessment robot (BAR-TM) that enables assessment of balancin...

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BMC psychiatry
BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classical between-group comparisons, machine learning can identify subtle disease patterns on a single subject level, which could help realize the potential...