A5066895530- ECG Monitoring and Analysis
- Anomaly Detection Techniques and Applications
- EEG and Brain-Computer Interfaces
- COVID-19 diagnosis using AI
- AI in cancer detection
- Heart Rate Variability and Autonomic Control
- Cardiac electrophysiology and arrhythmias
VinUniversity
2022-2023
Recent years have experienced phenomenal growth in computer-aided diagnosis systems based on machine learning algorithms for anomaly detection tasks the medical image domain. However, performance of these greatly depends quality labels since subjectivity a single annotator might decline certainty datasets. In order to alleviate this problem, aggregating from multiple radiologists with different levels expertise has been established. particular, under reliance their own biases and proficiency...
The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, raising need to develop novel tools provide rapid and cost-effective screening diagnosis. Clinical reports indicated that infection may cause cardiac injury, electrocardiograms (ECG) serve as a diagnostic biomarker for COVID-19. This study aims utilize ECG signals detect automatically. We propose method extract from paper records, which are then fed into one-dimensional convolution neural network (1D-CNN)...
An increasing number of people are being diagnosed with cardiovascular diseases (CVDs), the leading cause death globally. The gold standard for identifying these heart problems is via electrocardiogram (ECG). 12-lead ECG widely used in clinical practice and most current research. However, using fewer leads can make more pervasive as it be integrated portable or wearable devices. This article introduces two novel techniques to improve performance deep learning system 3-lead classification,...