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 …
Screening and diagnosis of cardiovascular disease using artificial intelligence-enabled cardiac magnetic resonance imaging
Cardiac magnetic resonance imaging (CMR) is the gold standard for cardiac function
assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However …
assessment and plays a crucial role in diagnosing cardiovascular disease (CVD). However …
Machine learning-based predictive models for detection of cardiovascular diseases
Cardiovascular diseases present a significant global health challenge that emphasizes the
critical need for developing accurate and more effective detection methods. Several studies …
critical need for developing accurate and more effective detection methods. Several studies …
Breast cancer dataset, classification and detection using deep learning
Incorporating scientific research into clinical practice via clinical informatics, which includes
genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment …
genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment …
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 …
A novel attention-based cross-modal transfer learning framework for predicting cardiovascular disease
NK Karthikeyan - Computers in Biology and Medicine, 2024 - Elsevier
Cardiovascular disease (CVD) remains a leading cause of death globally, presenting
significant challenges in early detection and treatment. The complexity of CVD arises from its …
significant challenges in early detection and treatment. The complexity of CVD arises from its …
Diagnosis of cardiovascular diseases by ensemble optimization deep learning techniques
Cardiovascular disease (CVD) is a variety of diseases that affect the blood vessels and the
heart. The authors propose a set of deep learning inspired by the approach used in CVD …
heart. The authors propose a set of deep learning inspired by the approach used in CVD …
Micronano Synergetic Three-Dimensional Bioelectronics: A Revolutionary Breakthrough Platform for Cardiac Electrophysiology
Cardiovascular diseases (CVDs) are the leading cause of mortality and therefore pose a
significant threat to human health. Cardiac electrophysiology plays a crucial role in the …
significant threat to human health. Cardiac electrophysiology plays a crucial role in the …