Computational modeling and experimental/clinical prediction of the complex signals during cardiac arrhythmias have the potential to lead to new approaches for prevention and treatment. Machine-learning (ML) and deep-learning approaches can be used fo...
Photonic spiking neural networks (PSNNs) potentially offer exceptionally high throughput and energy efficiency compared to their electronic neuromorphic counterparts while maintaining their benefits in terms of event-driven computing capability. Whil...
Mathematical biosciences and engineering : MBE
May 20, 2022
With the development of the field of survival analysis, statistical inference of right-censored data is of great importance for the study of medical diagnosis. In this study, a right-censored data survival prediction model based on an improved compos...
SIGNIFICANCE: To achieve early detection of osteoporosis, a simple bone densitometry method using optics was proposed. However, individual differences in soft tissue structure and optical properties can cause errors in quantitative bone densitometry....
Mathematical biosciences and engineering : MBE
Apr 27, 2022
Estimating material properties of personalized human left ventricular (LV) modelling is a central problem in biomechanical studies. In this work we use deep learning (DL) method to evaluating the passive myocardial mechanical properties inversely. In...
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Apr 25, 2022
The finite element method is a new method to study the mechanism of brain injury caused by blunt instruments. But it is not easy to be applied because of its technology barrier of time-consuming and strong professionalism. In this study, a rapid and ...
Mathematical biosciences and engineering : MBE
Apr 22, 2022
In this study, an adaptive modified reaching law-based switch controller design was developed for robotic manipulator systems using the disturbance observer (DO) approach. Firstly, a standard DO is employed to estimate the unknown disturbances of the...
Time-delayed reservoir computing (RC) is a brain inspired paradigm for processing temporal information, with simplification in the network's architecture using virtual nodes embedded in a temporal delay line. In this work, a novel, to the best of our...
In a neuron network, synapses update individually using local information, allowing for entirely decentralized learning. In contrast, elements in an artificial neural network are typically updated simultaneously using a central processor. Here, we in...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.