Background Computational models on the basis of deep neural networks are increasingly used to analyze health care data. However, the efficacy of traditional computational models in radiology is a matter of debate. Purpose To evaluate the accuracy and...
BACKGROUND: Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools.
Medical & biological engineering & computing
Jun 15, 2019
Due to its capabilities in analysing injury risk, the ability to analyse an athlete's ground reaction force and joint moments is of high interest in sports biomechanics. However, using force plates for the kinetic measurements influences the athlete'...
This paper proposes a sensitive, sample preparation-free, rapid, and low-cost method for the detection of the B-rapidly accelerated fibrosarcoma (BRAF) gene mutation involving a substitution of valine to glutamic acid at codon 600 (V600E) in colorect...
Computer methods and programs in biomedicine
Jun 14, 2019
BACKGROUND AND OBJECTIVES: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance ...
The fast identification and quantification of illicit drugs in biofluids are of great significance in clinical detection. However, existing drug detection strategies cannot fully meet clinical needs, and the on-site identification and quantification ...
A novel method to detect and classify several classes of diseased and healthy lung tissue in CT (Computed Tomography), based on the fusion of Riesz and deep learning features, is presented. First, discriminative parametric lung tissue texture signatu...
BACKGROUND: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human...
A natural language processing (NLP) algorithm to extract microbial keratitis morphology measurements from the electronic health record (EHR) was 75-96% sensitive and 91%-96% specific. NLP accurately extracts data from the corneal exam free-text EHR f...
PURPOSE: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).
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