AI Medical Compendium Topic:
Models, Theoretical

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Modeling of dielectric elastomer oscillators for soft biomimetic applications.

Bioinspiration & biomimetics
Biomimetic, entirely soft robots with animal-like behavior and integrated artificial nervous systems will open up totally new perspectives and applications. However, until now, most presented studies on soft robots were limited to only partly soft de...

Transductive Joint-Knowledge-Transfer TSK FS for Recognition of Epileptic EEG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Intelligent recognition of electroencephalogram (EEG) signals is an important means to detect seizure. Traditional methods for recognizing epileptic EEG signals are usually based on two assumptions: 1) adequate training examples are available for mod...

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

BMC medical informatics and decision making
BACKGROUND: Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthca...

A Novel Soft Pneumatic Artificial Muscle with High-Contraction Ratio.

Soft robotics
There is a growing interest in soft actuators for human-friendly robotic applications. However, it is very challenging for conventional soft actuators to achieve both a large working distance and high force. To address this problem, we present a high...

Detection of genetic cardiac diseases by Ca transient profiles using machine learning methods.

Scientific reports
Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have revolutionized cardiovascular research. Abnormalities in Ca transients have been evident in many cardiac disease models. We have shown earlier that, by exploiting computation...

A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus.

Scientific reports
Memristive systems have gained considerable attention in the field of neuromorphic engineering, because they allow the emulation of synaptic functionality in solid state nano-physical systems. In this study, we show that memristive behavior provides ...

Time series model for forecasting the number of new admission inpatients.

BMC medical informatics and decision making
BACKGROUND: Hospital crowding is a rising problem, effective predicting and detecting managment can helpful to reduce crowding. Our team has successfully proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and ...

Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

PloS one
Recent studies on machine learning technology have reported successful performances in some visual and auditory recognition tasks, while little has been reported in the field of olfaction. In this paper we report computational methods to predict the ...

Learning-Based Cell Injection Control for Precise Drop-on-Demand Cell Printing.

Annals of biomedical engineering
Drop-on-demand (DOD) printing is widely used in bioprinting for tissue engineering because of little damage to cell viability and cost-effectiveness. However, satellite droplets may be generated during printing, deviating cells from the desired posit...

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

Psychological review
We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the inpu...