Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It is commonly assumed that training CNNs requires large amounts of annotated data. This is a bottleneck in many medical applications where annotation r...
Magnetic micro/nanorobots attracted much attention in biomedical fields because of their precise movement, manipulation, and targeting abilities. However, there is a lack of research on intelligent micro/nanorobots with stimuli-responsive drug delive...
Image compression is used in several clinical organizations to help address the overhead associated with medical imaging. These methods reduce file size by using a compact representation of the original image. This study aimed to analyze the impact o...
Postpartum depression (PPD) is a detrimental health condition that affects 12% of new mothers. Despite negative effects on mothers' and children's health, many women do not receive adequate care. Preventive interventions are cost-efficient among high...
BACKGROUND: Biomedical ontologies contain a wealth of metadata that constitutes a fundamental infrastructural resource for text mining. For several reasons, redundancies exist in the ontology ecosystem, which lead to the same entities being described...
BACKGROUND: Breast cancer is amongst the 10 first causes of death in women worldwide. Around 20% of patients are misdiagnosed leading to early metastasis, resistance to treatment and relapse. Many clinical and gene expression profiles have been succe...
BACKGROUND: artificial intelligence (AI) for cellular phenotyping diagnosis of nasal polyps by whole-slide imaging (WSI) is lacking. We aim to establish an AI chronic rhinosinusitis evaluation platform 2.0 (AICEP 2.0) to obtain the proportion of infl...
Theoretically-driven models of suicide have long guided suicidology; however, an approach employing machine learning models has recently emerged in the field. Some have suggested that machine learning models yield improved prediction as compared to t...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 12, 2021
In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filter. For (1), we design a deep network with both progressive rethinking and collaborative learning me...
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