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OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings
In the real-world clinical setting, OpenClinicalAI significantly outperforms the state-of-the-art AI system.
LoadCNN: A Low Training Cost Deep Learning Model for Day-Ahead Individual Residential Load Forecasting
As a consequence, the deep learning methods are difficult to be popularized and applied in the real smart grid environment.
EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction
The precise diagnosis is of great significance in developing precise treatment plans to restore neck function and reduce the burden posed by the cervical spondylosis (CS).
A new direction to promote the implementation of artificial intelligence in natural clinical settings
Artificial intelligence (AI) researchers claim that they have made great `achievements' in clinical realms.
EasiCSDeep: A deep learning model for Cervical Spondylosis Identification using surface electromyography signal
In this paper, we present an intelligent method based on the deep learning to identify CS, using the surface electromyography (sEMG) signal.
