[HTML][HTML] A systematic literature review and analysis of deep learning algorithms in mental disorders

G Arji, L Erfannia, M Hemmat - Informatics in medicine unlocked, 2023 - Elsevier
Introduction Mental disorders are the main cause of mortality and morbidity worldwide. Deep
learning offers a considerable promise for mental health diagnosis and risk assessment. The …

Improved UNet deep learning model for automatic detection of lung cancer nodules

V Kumar, BR Altahan, T Rasheed… - Computational …, 2023 - Wiley Online Library
Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent
kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred …

The early warning mechanism of public health emergencies through whistleblowing: a perspective based on considering the uncertainty of risk perception

R Ma, J Liu, S An - Risk management and healthcare policy, 2023 - Taylor & Francis
Purpose During the early warning period of public health emergencies, the information
released by whistleblowers on the risk posed by the given event can reduce uncertainty in …

Machine Learning for Mental Health: A Systematic Study of Seven Approaches for Detecting Mental Disorders

M Nadeem, J Rashid, H Moon… - … Technical Conference on …, 2023 - ieeexplore.ieee.org
Mental disorders are a prevalent issue among teenagers. The widespread use of
smartphones and social media has revolutionized the way individuals communicate and …

Virtual emotional gestures to assist in the examination of the mental health of the deaf‐mutes

H Liang, H Xu, Y Wang, J Pan, J Fu… - … Animation and Virtual …, 2023 - Wiley Online Library
The particular characteristics of deaf‐mutes make them more likely to have mental health
problems. Due to their particular way of communication, it is more difficult for them to deal …

Content‐Based Audio Classification and Retrieving Using Modified Bacterial Foraging Optimization Algorithm

AK Samha, GH Alshammri… - Computational …, 2023 - Wiley Online Library
Audio classification and retrieval has been recognized as a fascinating field of endeavor for
as long as it has existed due to the topic of identifying and choosing the most useful audio …

Real-Time Sentiment Analysis and Spam Detection Using Machine Learning and Deep Learning

MM Abdulhasan, H Alchilibi, MA Mohammed… - … Conference on Data …, 2023 - Springer
In our environment, constant information exposure is required and done in a certain way.
Twitter, Facebook, and Quora struggle to handle spam accounts. Automated software …

Electrocardiogram Feature Based Heart Arrhythmia Detection Using Machine Learning and Apache Spark

P Singhal, RK Yadav - 2023 - researchsquare.com
Heart arrhythmias are the main cause of death worldwide. Electrocardiogram (ECG) results
can be used to identify arrhythmias, or irregularities in the heart's rhythm. Because …

Bayesian-Enhanced EEG Signal Analysis for Epileptic Seizure Recognition: A 1D-CNN LSTM Approach

M Jain, H Bhardwaj, A Srivastav - 2024 11th International …, 2024 - ieeexplore.ieee.org
The intricate neurological condition known as epilepsy, which is common across the world,
presents consid-erable difficulties in accurately identifying and differentiating between non …

Dementia Alzheimer's Disease Diagnosis Using Convolutional Neural Networks on Two-Dimensional MRI Slices.

S Chaudhary, R Nehra, K Kumar… - Revue d' …, 2024 - search.ebscohost.com
The major goal of this work is to explore the performance of convolutional neural networks
(CNNs) in identifying patterns symptomatic of Alzheimer's disease. This approach proposes …