Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review

M Jafari, A Shoeibi, M Khodatars, N Ghassemi… - Computers in Biology …, 2023 - Elsevier
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 …

[HTML][HTML] Multi-modality cardiac image computing: A survey

L Li, W Ding, L Huang, X Zhuang, V Grau - Medical Image Analysis, 2023 - Elsevier
Multi-modality cardiac imaging plays a key role in the management of patients with
cardiovascular diseases. It allows a combination of complementary anatomical …

The role of artificial intelligence in improving patient outcomes and future of healthcare delivery in cardiology: a narrative review of the literature

D Gala, H Behl, M Shah, AN Makaryus - Healthcare, 2024 - mdpi.com
Cardiovascular diseases exert a significant burden on the healthcare system worldwide.
This narrative literature review discusses the role of artificial intelligence (AI) in the field of …

Applications of AI in multi-modal imaging for cardiovascular disease

M Milosevic, Q Jin, A Singh, S Amal - Frontiers in radiology, 2024 - frontiersin.org
Data for healthcare is diverse and includes many different modalities. Traditional
approaches to Artificial Intelligence for cardiovascular disease were typically limited to …

AI-based computer vision using deep learning in 6G wireless networks

MM Kamruzzaman, O Alruwaili - Computers and Electrical Engineering, 2022 - Elsevier
Modern businesses benefit significantly from advances in computer vision technology, one
of the important sectors of artificially intelligent and computer science research. Advanced …

Deep learning-derived myocardial strain

AC Kwan, EW Chang, I Jain, J Theurer, X Tang… - JACC: Cardiovascular …, 2024 - Elsevier
Background Echocardiographic strain measurements require extensive operator experience
and have significant intervendor variability. Creating an automated, open-source, vendor …

Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions--A Systematic Review

MS Ali, MM Ahsan, L Tasnim, S Afrin, K Biswas… - arXiv preprint arXiv …, 2024 - arxiv.org
Data privacy has become a major concern in healthcare due to the increasing digitization of
medical records and data-driven medical research. Protecting sensitive patient information …

A Review on Various CNN-based Approaches for Facial Expression Recognition

V Chand, A Chrisanthus, A Thampi… - 2023 International …, 2023 - ieeexplore.ieee.org
Facial emotion recognition is a rapidly developing field that has the potential to revolutionize
the way people interact with technology and each other. It uses advanced algorithms to …

What Matters in Radiological Image Segmentation? Effect of Segmentation Errors on the Diagnostic Related Features

Z Chen, J Chen, J Zhao, B Liu, S Jiang, D Si… - Journal of Digital …, 2023 - Springer
Segmentation is a crucial step in extracting the medical image features for clinical diagnosis.
Though multiple metrics have been proposed to evaluate the segmentation performance …

[PDF][PDF] Automated Diagnosis of Cardiovascular Disease on Cardiovascular Magnetic Resonance Imaging Using Deep Learning Models: A Review

M Jafari, A Shoeibi, M Khodatars, N Ghassemi… - 2023 - opus.lib.uts.edu.au
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. CVDs appear with minor symptoms and progressively get worse. The …