In this work, we present a multi-modal machine learning method to automate early glaucoma diagnosis. The proposed methodology introduces two novel aspects for automated diagnosis not previously explored in the literature: simultaneous use of ocular f...
Intraventricular vector flow mapping (VFM) is an increasingly adopted echocardiographic technique that derives time-resolved two-dimensional flow maps in the left ventricle (LV) from color-Doppler sequences. Current VFM models rely on kinematic const...
PURPOSE: Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (C...
Journal of the Air & Waste Management Association (1995)
Dec 12, 2024
Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more ...
Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hindering their ability to live healthy lives and participate in daily activities. It is challenging to diagnose these disorders due to a lack of reliable d...
Given the crucial role of thiols in maintaining normal physiological functions, it is essential to establish a high-throughput and sensitive analytical method to identify and quantify various thiols accurately. Inspired by the iron porphyrin active c...
The ever-increasing volume of complex data poses significant challenges to conventional sequential global processing methods, highlighting their inherent limitations. This computational burden has catalyzed interest in neuromorphic computing, particu...
Artificial neural networks provide a powerful paradigm for nonbiological information processing. To understand whether similar principles could enable computation within living cells, we combined de novo-designed protein heterodimers and engineered v...
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...
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