Results 251 to 260 of about 2,093,786 (309)

Flexible self-rectifying synapse array for energy-efficient edge multiplication in electrocardiogram diagnosis. [PDF]

Nat Commun
Lee Y, Rhee H, Kim G, Cheong WH, Kim DH, Song H, Kay SN, Lee J, Kim KM.   +8 more
europepmc   +1 more source

Deep learning for electrocardiogram interpretation: Bench to bedside. [PDF]

Eur J Clin Invest
Schots BBS, Pizarro CS, Arends BKO, Oerlemans MIFJ, Ahmetagić D, van der Harst P, van Es R.   +6 more
europepmc   +1 more source

Acupuncture might enhance word recognition scores in a patient with hearing loss: a case report and literature review. [PDF]

Front Neurosci
Fang K, Jiang D, Zhao M, Hu H, Li Y, Gao H, Zhou J.   +6 more
europepmc   +1 more source

Translational approach to ventricular innervation: the posterior descending ganglionated plexus. [PDF]

Europace
Kahle AK, Klatt N, Scherschel K, Jungen C, Kuklik P, Alken FA, Klöcker N, Willems S, Weber E, Boeken U, Lichtenberg A, Bernhardt A, Hakmi S, Pauza DH, Meyer C.   +14 more
europepmc   +1 more source

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Excitable Membranes and Neural Conduction

, 2013
Neural information processing is based on three cellular mechanisms, i.e., the excitability of neural membranes, the spatio-temporal integration of activities on dendritic trees, and synaptic transmission. The basic element of neural activity is the action potential, which is a binary event, being either present or absent, much as the electrical ...
H. Mallot
semanticscholar   +3 more sources

Multi-domain physics-informed neural networks for solving transient heat conduction problems in multilayer materials

Journal of Applied Physics, 2023
In this paper, we aim to numerically resolve linear and nonlinear transient heat conduction problems in multilayer composite materials using a deep learning method called multi-domain physics-informed neural networks (MDPINNs).
Benrong Zhang, Fajie Wang, Lin Qiu
semanticscholar   +1 more source

Multi-domain physics-informed neural network for solving forward and inverse problems of steady-state heat conduction in multilayer media

The Physics of Fluids, 2022
In this paper, a novel deep learning technique, called multi-domain physics-informed neural network (M-PINN), is presented to solve forward and inverse problems of steady-state heat conduction in multilayer media.
Benrong Zhang, Guozheng Wu, Y. Gu, Xiao Wang, Fajie Wang   +4 more
semanticscholar   +1 more source

Signal Conduction and Neural Conduction

, 2017
Qinyi Zhao
semanticscholar   +2 more sources

Non-Fourier Heat Conduction based on Self-Adaptive Weight Physics-Informed Neural Networks

Cybersecurity and Cyberforensics Conference, 2021
This paper establishes the non-Fourier heat conduction model to describe the heat transfer process of mono-crystalline silicon under the condition of unstable thermal field and thermal shock in the Czochralski method.
Shuyan Shi, Ding Liu, Zhongdan Zhao
semanticscholar   +1 more source