Blood pressure detection using CNN-LSTM model
Blood pressure (BP) is a key indication that needs to be checked on a regular basis. For
maintaining a healthy life normal blood pressure is essential, and a continuous change can …
maintaining a healthy life normal blood pressure is essential, and a continuous change can …
A convolutional neural network approach for diabetic retinopathy classification
Diabetic Retinopathy (DR) is a kind of problem which affects diabetic patients, particularly
those at their age of working, and can result in vision impairment and possibly irreversible …
those at their age of working, and can result in vision impairment and possibly irreversible …
AI-based epileptic seizure detection and prediction in internet of healthcare things: a systematic review
Epilepsy is a neurological condition affecting around 50 million individuals worldwide,
reported by the World Health Organization. This is identified as a hypersensitive disease by …
reported by the World Health Organization. This is identified as a hypersensitive disease by …
Liver disease prediction using machine learning classification techniques
Machine Learning is a process which is used to discover patterns in huge data/large data
set to enable decision, thereby allowing machines to go through a learning process (ie …
set to enable decision, thereby allowing machines to go through a learning process (ie …
Automated Seizure Detection using Theta Band
The EEG signal is made up of numerous frequency bands that characterize human
behaviours like emotion, attentiveness, and sleep status, among others. In order to detect …
behaviours like emotion, attentiveness, and sleep status, among others. In order to detect …
A LSTM-CNN Model for Epileptic Seizures Detection using EEG Signal
Neurologists visually inspect electroencephalogram (EEG) reports to get the epilepsy
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …
Methodologies and evaluation of electronic travel aids for the visually impaired people: a review
Technological advancements have widely contributed to navigation aids. However, their
large-scale adaptation for navigation solutions for visually impaired people haven't been …
large-scale adaptation for navigation solutions for visually impaired people haven't been …
Hybrid attention network for epileptic EEG classification
Y Zhao, J He, F Zhu, T Xiao, Y Zhang… - … Journal of Neural …, 2023 - World Scientific
Automatic seizure detection from electroencephalography (EEG) based on deep learning
has been significantly improved. However, existing works have not adequately excavate the …
has been significantly improved. However, existing works have not adequately excavate the …
Artificial neural network model using short-term fourier transform for epilepsy seizure detection
Epilepsy is a neurological illness that can strike anyone at any time in their life. However, a
person with epilepsy will experience frequent to uncommon seizures, resulting in death …
person with epilepsy will experience frequent to uncommon seizures, resulting in death …
CNN based framework for detection of epileptic seizures
Epilepsy is a common neurological disease that uses electroencephalogram (EEG) data for
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …