Advancing medical imaging informatics by deep learning-based domain adaptation
Introduction: There has been a rapid development of deep learning (DL) models for medical
imaging. However, DL requires a large labeled dataset for training the models. Getting large …
imaging. However, DL requires a large labeled dataset for training the models. Getting large …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
COVID-19 automatic diagnosis with radiographic imaging: Explainable attention transfer deep neural networks
Researchers seek help from deep learning methods to alleviate the enormous burden of
reading radiological images by clinicians during the COVID-19 pandemic. However …
reading radiological images by clinicians during the COVID-19 pandemic. However …
Parse: Pairwise alignment of representations in semi-supervised eeg learning for emotion recognition
G Zhang, V Davoodnia… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We propose pairwise alignment of representations for semi-supervised
Electroencephalogram (EEG) learning (PARSE), a novel semi-supervised architecture for …
Electroencephalogram (EEG) learning (PARSE), a novel semi-supervised architecture for …
Systematic review of advanced AI methods for improving healthcare data quality in post COVID-19 Era
At the beginning of the COVID-19 pandemic, there was significant hype about the potential
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …
Choice over effort: Mapping and diagnosing augmented whole slide image datasets with training dynamics
In pediatric heart transplantation, manual annotations with interob-server and intraobserver
variability among cardiovascular pathology experts lead to significant disagreements about …
variability among cardiovascular pathology experts lead to significant disagreements about …
Generating region of interests for invasive breast cancer in histopathological whole-slide-image
The detection of the region of interests (ROIs) on Whole Slide Images (WSIs) is one of the
primary steps in computer-aided cancer diagnosis and grading. Early and accurate …
primary steps in computer-aided cancer diagnosis and grading. Early and accurate …
Holistic semi-supervised approaches for eeg representation learning
Recently, supervised methods, which often require substantial amounts of class labels, have
achieved promising results for EEG representation learning. However, labeling EEG data is …
achieved promising results for EEG representation learning. However, labeling EEG data is …
Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification
Objective Pneumothorax is an acute thoracic disease caused by abnormal air collection
between the lungs and chest wall. Recently, artificial intelligence (AI), especially deep …
between the lungs and chest wall. Recently, artificial intelligence (AI), especially deep …
Efficient detection of lesions during endoscopy
Endoscopy is a very important procedure in the medical field. It is used to detect almost any
diseases associated with the gastrointestinal (GI) tract. Hence, the current work attempts to …
diseases associated with the gastrointestinal (GI) tract. Hence, the current work attempts to …