Knowledge discovery in medicine: Current issue and future trend
N Esfandiari, MR Babavalian, AME Moghadam… - Expert Systems with …, 2014 - Elsevier
Data mining is a powerful method to extract knowledge from data. Raw data faces various
challenges that make traditional method improper for knowledge extraction. Data mining is …
challenges that make traditional method improper for knowledge extraction. Data mining is …
Diagnosis of human psychological disorders using supervised learning and nature-inspired computing techniques: a meta-analysis
P Kaur, M Sharma - Journal of medical systems, 2019 - Springer
A psychological disorder is a mutilation state of the body that intervenes the imperative
functioning of the mind or brain. In the last few years, the number of psychological disorders …
functioning of the mind or brain. In the last few years, the number of psychological disorders …
Optimized deep learning for EEG big data and seizure prediction BCI via internet of things
MP Hosseini, D Pompili, K Elisevich… - … Transactions on Big …, 2017 - ieeexplore.ieee.org
A brain-computer interface (BCI) for seizure prediction provides a means of controlling
epilepsy in medically refractory patients whose site of epileptogenicity cannot be resected …
epilepsy in medically refractory patients whose site of epileptogenicity cannot be resected …
Separating the polynomial-time hierarchy by oracles
ACC Yao - 26th Annual Symposium on Foundations of …, 1985 - ieeexplore.ieee.org
We present exponential lower bounds on the size of depth-k Boolean circuits for computing
certain functions. These results imply that there exists an oracle set A such that, relative to A …
certain functions. These results imply that there exists an oracle set A such that, relative to A …
[HTML][HTML] A machine learning system for automated whole-brain seizure detection
Epilepsy is a chronic neurological condition that affects approximately 70 million people
worldwide. Characterised by sudden bursts of excess electricity in the brain, manifesting as …
worldwide. Characterised by sudden bursts of excess electricity in the brain, manifesting as …
Reservoir computing models based on spiking neural P systems for time series classification
H Peng, X Xiong, M Wu, J Wang, Q Yang… - Neural Networks, 2024 - Elsevier
Nonlinear spiking neural P (NSNP) systems are neural-like membrane computing models
with nonlinear spiking mechanisms. Because of this nonlinear spiking mechanism, NSNP …
with nonlinear spiking mechanisms. Because of this nonlinear spiking mechanism, NSNP …
Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing
Background and objective Multimodal data analysis and large-scale computational
capability is entering medicine in an accelerative fashion and has begun to influence …
capability is entering medicine in an accelerative fashion and has begun to influence …
An efficient system for heart disease prediction using hybrid OFBAT with rule-based fuzzy logic model
The objective of the work is to predict heart disease using computing techniques like an
oppositional firefly with BAT and rule-based fuzzy logic (RBFL). The system would help the …
oppositional firefly with BAT and rule-based fuzzy logic (RBFL). The system would help the …
Scalp EEG epileptogenic zone recognition and localization based on long-term recurrent convolutional network
W Liang, H Pei, Q Cai, Y Wang - Neurocomputing, 2020 - Elsevier
The scalp electroencephalogram (EEG), a non-invasive measure of brain's electrical activity,
is commonly used ancillary test to aide in the diagnosis of epilepsy. Usually, neurologists …
is commonly used ancillary test to aide in the diagnosis of epilepsy. Usually, neurologists …
Functional echo state network for time series classification
Echo state networks (ESNs) are a new approach to recurrent neural networks (RNNs) that
have been successfully applied in many domains. Nevertheless, an ESN is a predictive …
have been successfully applied in many domains. Nevertheless, an ESN is a predictive …