AIMC Topic: Probability
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The Probability of Ischaemic Stroke Prediction with a Multi-Neural-Network Model.
Sensors (Basel, Switzerland)
Sep 3, 2020
As is known, cerebral stroke has become one of the main diseases endangering people's health; ischaemic strokes accounts for approximately 85% of cerebral strokes. According to research, early prediction and prevention can effectively reduce the inci...
Rule-based automatic diagnosis of thyroid nodules from intraoperative frozen sections using deep learning.
Artificial intelligence in medicine
Aug 9, 2020
Frozen sections provide a basis for rapid intraoperative diagnosis that can guide surgery, but the diagnoses often challenge pathologists. Here we propose a rule-based system to differentiate thyroid nodules from intraoperative frozen sections using ...
Dr. Answer AI for prostate cancer: Clinical outcome prediction model and service.
PloS one
Aug 5, 2020
OBJECTIVES: The importance of clinical outcome prediction models using artificial intelligence (AI) is being emphasized owing to the increasing necessity of developing a clinical decision support system (CDSS) employing AI. Therefore, in this study, ...
Recurrent probabilistic neural network-based short-term prediction for acute hypotension and ventricular fibrillation.
Scientific reports
Jul 20, 2020
In this paper, we propose a novel method for predicting acute clinical deterioration triggered by hypotension, ventricular fibrillation, and an undiagnosed multiple disease condition using biological signals, such as heart rate, RR interval, and bloo...
Expressing uncertainty in Human-Robot interaction.
PloS one
Jul 16, 2020
Most people struggle to understand probability which is an issue for Human-Robot Interaction (HRI) researchers who need to communicate risks and uncertainties to the participants in their studies, the media and policy makers. Previous work showed tha...
Asynchronous dissipative filtering for nonhomogeneous Markov switching neural networks with variable packet dropouts.
Neural networks : the official journal of the International Neural Network Society
Jul 15, 2020
This work focuses on the problem of asynchronous filtering for nonhomogeneous Markov switching neural networks with variable packet dropouts (VPDs). The discrete-time nonhomogeneous Markov process is adopted to depict the modes switching of target pl...
Neural networks of different species, brain areas and states can be characterized by the probability polling state.
The European journal of neuroscience
Jul 11, 2020
Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from ...
Fixed-time synchronization of stochastic memristor-based neural networks with adaptive control.
Neural networks : the official journal of the International Neural Network Society
Jul 10, 2020
In this study, we consider the fixed-time synchronization problem for stochastic memristor-based neural networks (MNNs) via two different controllers. First, a new stochastic differential equation is established using differential inclusions and set-...
Delay-distribution-dependent state estimation for neural networks under stochastic communication protocol with uncertain transition probabilities.
Neural networks : the official journal of the International Neural Network Society
Jul 6, 2020
In this paper, the protocol-based remote state estimation problem is considered for a kind of delayed artificial neural networks. The random time-varying delays fall into certain intervals with known probability distributions. For the sake of reducin...
Artificial neural network based isotopic analysis of airborne radioactivity measurement for radiological incident detection.
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Jul 5, 2020
Responders need tools to rapidly detect and identify airborne alpha radioactivity during consequence management scenarios. Traditional continuous air monitoring systems used for this purpose compute the net counts in various energy windows to determi...
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