AIMC Topic: Databases, Factual

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EDSRNet: An Enhanced Decoder Semantic Recovery Network for 2D Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In recent years, with the advancement of medical imaging technology, medical image segmentation has played a key role in assisting diagnosis and treatment planning. Current deep learning-based medical image segmentation methods mainly adopt encoder-d...

PFPRNet: A Phase-Wise Feature Pyramid With Retention Network for Polyp Segmentation.

IEEE journal of biomedical and health informatics
Early detection of colonic polyps is crucial for the prevention and diagnosis of colorectal cancer. Currently, deep learning-based polyp segmentation methods have become mainstream and achieved remarkable results. Acquiring a large number of labeled ...

ContraSurv: Enhancing Prognostic Assessment of Medical Images via Data-Efficient Weakly Supervised Contrastive Learning.

IEEE journal of biomedical and health informatics
Prognostic assessment remains a critical challenge in medical research, often limited by the lack of well-labeled data. In this work, we introduce ContraSurv, a weakly-supervised learning framework based on contrastive learning, designed to enhance p...

Partial Annotation Learning for Biomedical Entity Recognition.

IEEE journal of biomedical and health informatics
Named Entity Recognition (NER) is a key task to support biomedical research. In Biomedical Named Entity Recognition (BioNER), obtaining high-quality expert annotated data is laborious and expensive, leading to the development of automatic approaches ...

Predicting Clinical Anticancer Drug Response of Patients by Using Domain Alignment and Prototypical Learning.

IEEE journal of biomedical and health informatics
Anticancer drug response prediction is crucial in developing personalized treatment plans for cancer patients. However, High-quality patient anticancer drug response data are scarce and cell line data and patient data have different distributions, mo...

Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.

Computers in biology and medicine
Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate intervention due to neuropsychological issues. However, existing approaches such as polysomnography, considered the most reliable and accurate test to de...

Systematic collection, annotation, and pattern analysis of viral vaccines in the VIOLIN vaccine knowledgebase.

Frontiers in cellular and infection microbiology
BACKGROUND: Viral vaccines have been proven significant in protecting us against viral diseases such as COVID-19. To better understand and design viral vaccines, it is critical to systematically collect, annotate, and analyse various viral vaccines a...

QMaxViT-Unet+: A query-based MaxViT-Unet with edge enhancement for scribble-supervised segmentation of medical images.

Computers in biology and medicine
The deployment of advanced deep learning models for medical image segmentation is often constrained by the requirement for extensively annotated datasets. Weakly-supervised learning, which allows less precise labels, has become a promising solution t...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

Journal of food protection
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...