Analysis of mental health during COVID-19 pandemic
S Singu - International Journal of Sustainable Development in …, 2022 - ijsdcs.com
As a major virus outbreak in the 21st century, the Coronavirus disease 2019 (COVID-19)
pandemic has led to unprecedented hazards to mental health globally. While psychological …
pandemic has led to unprecedented hazards to mental health globally. While psychological …
Automation of human behaviors and its prediction using machine learning
Prediction is a method of detecting a person's behavior toward online buying by evaluating
publically available evaluations on the web. Understanding expressive human …
publically available evaluations on the web. Understanding expressive human …
Blockchain platform to resolve security issues in IoT and smart networks
IoT provided a unified operating picture across a wide range of modern-day applications.
The operating image is accomplished thanks to improvements in wireless sensor network …
The operating image is accomplished thanks to improvements in wireless sensor network …
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 …
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 …
A novel method for diabetes classification and prediction with Pycaret
The incredible advances in biotechnology and public healthcare infrastructures have
resulted in a massive output of vital and sensitive healthcare data. Many fascinating trends …
resulted in a massive output of vital and sensitive healthcare data. Many fascinating trends …
Real-Time Detection of Cardiac Arrest Using Deep Learning
The leading cause of death worldwide is cardiac disease, which kills an estimated 27.9
million people each year and is responsible for 31% of all fatalities. Heart failure is …
million people each year and is responsible for 31% of all fatalities. Heart failure is …
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 …
Machine Learning-based Evaluation of Heart Rate Variability Response in Children with Autism Spectrum Disorder
VA Mohammed, MA Mohammed… - … and Smart Energy …, 2023 - ieeexplore.ieee.org
At present, various electronic devices are used to monitor human heart rates. However, its
functions are to avoid predicting the problems caused by heart rate variability in advance …
functions are to avoid predicting the problems caused by heart rate variability in advance …
An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model
MA Mohammed, MA Mohammed… - … , IoT and Security …, 2023 - ieeexplore.ieee.org
In general, cardiac arrest results in an inability to pump enough blood for the body's needs.
Through this, the organs and tissues get enough oxygen and nutrients for their metabolic …
Through this, the organs and tissues get enough oxygen and nutrients for their metabolic …