Year: 2024
Type: article
Abstract: Deep learning, a subset of machine learning inspired by the human brain, employs interconnected layers of artificial neurons to automatically extract meaningful patterns from complex datasets.Its ability to handle unstructured data like images, text, and sound makes it ideal for analysing sleep-related data.Millions worldwide suffer from sleep disorders, impacting health and well-being.This project explores deep learning's potential to revolutionize understanding, diagnosing, and treating these disorders.It outlines the steps involved in leveraging deep learning for insights from sleep-related datasets, addressing insomnia and sleep apnea affecting diverse demographics.The project aims to raise awareness among individuals, particularly in specific occupations, about the risks associated with sleep disorders.Through data analysis, it will construct a bar graph illustrating correlations between professions and the likelihood of developing insomnia or sleep apnea, facilitating informed decisions about sleep quality and testing.
Language: English
Topic: Sleep and related disorders
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4401507190