[HTML][HTML] Novel cuckoo search-based metaheuristic approach for deep learning prediction of depression
Depression is a common illness worldwide with doubtless severe implications. Due to the
absence of early identification and treatment for depression, millions of individuals …
absence of early identification and treatment for depression, millions of individuals …
[HTML][HTML] A deep learning-based comparative study to track mental depression from EEG data
A Sarkar, A Singh, R Chakraborty - Neuroscience Informatics, 2022 - Elsevier
Background Modern day's society is engaged in commitment-based and time-bound jobs.
This invites tension and mental depression among many people who are not able to cope …
This invites tension and mental depression among many people who are not able to cope …
[HTML][HTML] Depression diagnosis by deep learning using EEG signals: A systematic review
A Safayari, H Bolhasani - Medicine in Novel Technology and Devices, 2021 - Elsevier
Depression is considered by WHO as the main contributor to global disability and it poses
dangerous threats to approximately all aspects of human life, in particular public and private …
dangerous threats to approximately all aspects of human life, in particular public and private …
[HTML][HTML] A hybrid model for depression detection using deep learning
N Marriwala, D Chaudhary - Measurement: Sensors, 2023 - Elsevier
Millions of people are suffering from mental illness due to unavailability of early treatment
and services for depression detection. It is the major reason for anxiety disorder, bipolar …
and services for depression detection. It is the major reason for anxiety disorder, bipolar …
Automated EEG-based screening of depression using deep convolutional neural network
In recent years, advanced neurocomputing and machine learning techniques have been
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
[PDF][PDF] Predicting depression using deep learning and ensemble algorithms on raw twitter data
NP Shetty, B Muniyal, A Anand, S Kumar… - International Journal of …, 2020 - academia.edu
Social networking sites have become a habitual component, with sites like Twitter and
Facebook being the 7th and 2nd favorite sites having millions of subscribers [1]. Such sites …
Facebook being the 7th and 2nd favorite sites having millions of subscribers [1]. Such sites …
[HTML][HTML] Machine learning algorithms for depression: diagnosis, insights, and research directions
Over the years, stress, anxiety, and modern-day fast-paced lifestyles have had immense
psychological effects on people's minds worldwide. The global technological development …
psychological effects on people's minds worldwide. The global technological development …
[HTML][HTML] An in-depth analysis of machine learning approaches to predict depression
Among all the forms of psychological and mental disorders, depression is the most common
form. Nowadays a large number of youths and adults around the world suffer from …
form. Nowadays a large number of youths and adults around the world suffer from …
Hyper-parameter optimization of deep learning model for prediction of Parkinson's disease
S Kaur, H Aggarwal, R Rani - Machine Vision and Applications, 2020 - Springer
Neurodegenerative disorder such as Parkinson's disease (PD) is among the severe health
problems in our aging society. It is a neural disorder that affects people socially as well as …
problems in our aging society. It is a neural disorder that affects people socially as well as …
EEG-based deep learning model for the automatic detection of clinical depression
PP Thoduparambil, A Dominic… - Physical and Engineering …, 2020 - Springer
Clinical depression is a neurological disorder that can be identified by analyzing the
Electroencephalography (EEG) signals. However, the major drawback in using EEG to …
Electroencephalography (EEG) signals. However, the major drawback in using EEG to …