Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Emotion recognition in EEG signals using deep learning methods: A review
Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …
planning, reasoning, and other mental states. As a result, they are considered a significant …
Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional,
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack of …
[HTML][HTML] ALEC: active learning with ensemble of classifiers for clinical diagnosis of coronary artery disease
Invasive angiography is the reference standard for coronary artery disease (CAD) diagnosis
but is expensive and associated with certain risks. Machine learning (ML) using clinical and …
but is expensive and associated with certain risks. Machine learning (ML) using clinical and …
Identification of clinical features associated with mortality in COVID-19 patients
R Eskandarian, R Alizadehsani, M Behjati… - Operations Research …, 2023 - Springer
Understanding clinical features and risk factors associated with COVID-19 mortality is
needed to early identify critically ill patients, initiate treatments and prevent mortality. A …
needed to early identify critically ill patients, initiate treatments and prevent mortality. A …
Monitoring of cardiorespiratory parameters during sleep using a special holder for the accelerometer sensor
Sleep is extremely important for physical and mental health. Although polysomnography is
an established approach in sleep analysis, it is quite intrusive and expensive. Consequently …
an established approach in sleep analysis, it is quite intrusive and expensive. Consequently …
[HTML][HTML] ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis
C García-Vicente, GC Gutiérrez-Tobal… - Computers in Biology …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is
characterized by partial or complete obstruction of the upper airway during sleep. The …
characterized by partial or complete obstruction of the upper airway during sleep. The …
[HTML][HTML] Real-time acoustic simulation framework for tFUS: a feasibility study using navigation system
Transcranial focused ultrasound (tFUS), in which acoustic energy is focused on a small
region in the brain through the skull, is a non-invasive therapeutic method with high spatial …
region in the brain through the skull, is a non-invasive therapeutic method with high spatial …
Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals
V Barroso-García, M Fernández-Poyatos, B Sahelices… - Diagnostics, 2023 - mdpi.com
The high prevalence of sleep apnea and the limitations of polysomnography have prompted
the investigation of strategies aimed at automated diagnosis using a restricted number of …
the investigation of strategies aimed at automated diagnosis using a restricted number of …