In the past decade, the application of machine learning (ML) to healthcare has helped drive the automation of physician tasks as well as enhancements in clinical capabilities and access to care. This progress has emphasized that, from model developme...
Clinical chemistry and laboratory medicine
Jul 4, 2022
OBJECTIVES: Automated machine learning (AutoML) tools can help clinical laboratory professionals to develop machine learning models. The objective of this study was to develop a novel formula for the estimation of urine osmolality using an AutoML too...
The cross-lingual sentiment analysis (CLSA) aims to leverage label-rich resources in the source language to improve the models of a resource-scarce domain in the target language, where monolingual approaches based on machine learning usually suffer f...
In general, image restoration involves mapping from low-quality images to their high-quality counterparts. Such optimal mapping is usually nonlinear and learnable by machine learning. Recently, deep convolutional neural networks have proven promising...
Feature selection (FS) is an important data preprocessing technique in data mining and machine learning, which aims to select a small subset of information features to increase the performance and reduce the dimensionality. Particle swarm optimizatio...
Cancer is a major public health issue in the modern world. Breast cancer is a type of cancer that starts in the breast and spreads to other parts of the body. One of the most common types of cancer that kill women is breast cancer. When cells become ...
BACKGROUND: Machine learning is now a standard tool for cancer prediction based on gene expression data. However, deep learning is still new for this task, and there is no clear consensus about its performance and utility. Few experimental works have...
The detection of sleep apnea is critical for assessing sleep quality. It is also a proven biometric in diagnosing cardiovascular and other diseases. Recent studies have shown that radar-based non-contact vital sign monitoring system can effectively d...
IEEE transactions on pattern analysis and machine intelligence
Jul 1, 2022
Deep convolutional neural networks (DCNNs) are currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning. The success of DCNNs can be attributed to the careful selection of thei...
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