The human respiratory network is a vital system that provides oxygen supply and nourishment to the whole body. Pulmonary diseases can cause severe respiratory problems, leading to sudden death if not treated timely. Many researchers have utilized dee...
International journal of medical informatics
May 8, 2021
INTRODUCTION: We aimed to assess whether machine learning models are superior at predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional prediction model.
STUDY OBJECTIVE: To derive and internally and externally validate machine-learning models to predict emergency ambulance patient door-to-off-stretcher wait times that are applicable to a wide variety of emergency departments.
PURPOSE: To assess the potential of machine learning to predict low and high treatment demand in real life in patients with neovascular age-related macular degeneration (nAMD), retinal vein occlusion (RVO), and diabetic macular edema (DME) treated ac...
International journal of computer assisted radiology and surgery
May 8, 2021
PURPOSE: The most direct means of glaucoma screening is to use cup-to-disc ratio via colour fundus photography, the first step of which is the precise segmentation of the optic cup (OC) and optic disc (OD). In recent years, convolution neural network...
Advanced materials (Deerfield Beach, Fla.)
May 8, 2021
Touch sensing is among the most important sensing capabilities of a human, and the same is true for smart robotics. Current research on tactile sensors is mainly concentrated on electronic skin (e-skin), but e-skin is prone to be easily dirtied, dama...
BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning m...
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...
BACKGROUND: One challenge to train deep convolutional neural network (CNNs) models with whole slide images (WSIs) is providing the required large number of costly, manually annotated image regions. Strategies to alleviate the scarcity of annotated da...
Feature extraction from process signals enables process monitoring models to be effective in industrial processes. Deep learning presents extensive possibilities for extracting abstract features from image and visual data. However, the main inputs of...
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