PURPOSE: This study aimed to investigate the clinical usefulness of the enhanced-T1WI-based deep learning radiomics model (DLRM) in differentiating low- and high-grade meningiomas.
The retina is the deepest layer of texture covering the rear of the eye, recorded by fundus images. Vessel detection and segmentation are useful in disease diagnosis. The retina's blood vessels could help diagnose maladies such as glaucoma, diabetic ...
Recent breakthroughs in artificial intelligence (AI) have enabled machines to plan in tasks previously thought to be uniquely human. Meanwhile, the planning algorithms implemented by the brain itself remain largely unknown. Here, we review neural and...
Machine learning (ML) and especially deep learning (DL) with neural networks have demonstrated an amazing success in all sorts of AI problems, from computer vision to game playing, from natural language processing to speech and image recognition. In ...
The target recognition algorithm is one of the core technologies of Zanthoxylum pepper-picking robots. However, most existing detection algorithms cannot effectively detect Zanthoxylum fruit covered by branches, leaves and other fruits in natural sce...
Computational and mathematical methods in medicine
Jan 17, 2022
The objective of this study was to explore the application value of digital subtraction angiography (DSA) images optimized by deep learning algorithms in vascular restenosis patients undergoing cardiovascular intervention and their nursing efficacy. ...
IEEE journal of biomedical and health informatics
Jan 17, 2022
Till March 31st, 2021, the coronavirus disease 2019 (COVID-19) had reportedly infected more than 127 million people and caused over 2.5 million deaths worldwide. Timely diagnosis of COVID-19 is crucial for management of individual patients as well as...
IEEE journal of biomedical and health informatics
Jan 17, 2022
This study was designed to test if heart rate variability (HRV) data from preterm and full-term infants could be used to estimate their functional maturational age (FMA), using a machine learning model. We propose that the FMA, and its deviation from...
Motion classification can be performed using biometric signals recorded by electroencephalography (EEG) or electromyography (EMG) with noninvasive surface electrodes for the control of prosthetic arms. However, current single-modal EEG and EMG based ...
Some artificial intelligence algorithms have gained much attention in the rotating machinery fault diagnosis due to their robust nonlinear regression properties. In addition, existing deep learning algorithms are usually dependent on single signal fe...
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