AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic contrast-enhanced computed tomography (CT) of the abdomen, and to compare the image quality and lesion conspicuity among the reconstruction strength lev...
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely adopted to investigate functional abnormalities in brain diseases. Rs-fMRI data is unsupervised in nature because the psychological and neurological labels are coarse-grain...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 18, 2021
OBJECTIVES: The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is a promising tool for the evaluation of stroke expansion to determine suitability for reperfusion therapy. The aim of this study was to validate deep learning-based AS...
Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a ...
OBJECTIVE: To develop and evaluate the performance of a radiomics and machine learning model applied to ultrasound (US) images in predicting the risk of malignancy of a uterine mesenchymal lesion.
The advancement of artificial intelligence (AI) has facilitated its application in medical fields. However, there has been little research for AI-assisted endoscopy, despite the clinical significance of the efficiency and safety of cannulation in the...
OBJECTIVE: To assess whether machine learning algorithms (MLA) can predict eyes that will undergo rapid glaucoma progression based on an initial visual field (VF) test.
OBJECTIVE: The chest X-ray (CXR) is the most readily available and common imaging modality for the assessment of pneumonia. However, detecting pneumonia from chest radiography is a challenging task, even for experienced radiologists. An artificial in...
Childhood stunting is a serious public health concern in Bangladesh. Earlier research used conventional statistical methods to identify the risk factors of stunting, and very little is known about the applications and usefulness of machine learning (...
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healt...
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