AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 1071 to 1080 of 1118 articles

Neural Manifold Decoder for Acupuncture Stimulations With Representation Learning: An Acupuncture-Brain Interface.

IEEE journal of biomedical and health informatics Jun 1, 2025
Acupuncture stimulations in somatosensory system can modulate spatiotemporal brain activity and improve cognitive functions of patients with neurological disorders. The correlation between these somatosensory stimulations and dynamical brain response...
Humans Neural Networks, Computer Deep Learning Young Adult Electroencephalography Brain Adult Female Acupuncture Therapy Male Brain-Computer Interfaces Signal Processing, Computer-Assisted
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AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning.

IEEE journal of biomedical and health informatics Jun 1, 2025
Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resistance in cancer treatment. Given the high costs and time requirements of traditional biological experiments, there is an increasing need for computation...
Computational Biology Drug Resistance, Neoplasm RNA, Untranslated Algorithms Neoplasms Humans Machine Learning
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Hierarchical Multi-Class Group Correlation Learning Network for Medical Image Segmentation.

IEEE journal of biomedical and health informatics Jun 1, 2025
Hierarchical approaches have been tremendously successful at multi-label segmentation. However, it has been shown they may seriously suffer from the problem of only imposing constraints on shallow layers while ignoring deep relationships in the label...
Brain Brain Neoplasms Deep Learning Algorithms Databases, Factual Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Machine Learning
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Automated Ensemble Multimodal Machine Learning for Healthcare.

IEEE journal of biomedical and health informatics Jun 1, 2025
The application of machine learning in medicine and healthcare has led to the creation of numerous diagnostic and prognostic models. However, despite their success, current approaches generally issue predictions using data from a single modality. Thi...
Humans Neural Networks, Computer Machine Learning Image Interpretation, Computer-Assisted
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Semi-Supervised PARAFAC2 Decomposition for Computational Phenotyping Using Electronic Health Records.

IEEE journal of biomedical and health informatics Jun 1, 2025
Computational phenotyping uses data mining methods to extract clusters of clinical descriptors, known as phenotypes, from electronic health records (EHR). Tensor factorization methods are very effective in extracting meaningful patterns and have beco...
Phenotype Electronic Health Records Data Mining Supervised Machine Learning Humans Algorithms
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P2TC: A Lightweight Pyramid Pooling Transformer-CNN Network for Accurate 3D Whole Heart Segmentation.

IEEE journal of biomedical and health informatics Jun 1, 2025
Cardiovascular disease is a leading global cause of death, requiring accurate heart segmentation for diagnosis and surgical planning. Deep learning methods have been demonstrated to achieve superior performances in cardiac structures segmentation. Ho...
Imaging, Three-Dimensional Heart Neural Networks, Computer Deep Learning Humans
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TGAP-Net: Twin Graph Attention Pseudo-Label Generation for Weakly Supervised Semantic Segmentation.

IEEE journal of biomedical and health informatics Jun 1, 2025
Multilabel pathological tissue segmentation is a vital task in computational pathology that aims to semantically segment different tissues within pathological images. Fully and weakly supervised models have demonstrated impressive performances in thi...
Humans Supervised Machine Learning Image Interpretation, Computer-Assisted Semantics Algorithms Female
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Learning Sensor Sample-Reweighting for Dynamic Early-Exit Activity Recognition Via Meta Learning.

IEEE journal of biomedical and health informatics Jun 1, 2025
During recent years, dynamic early-exit has provided a promising paradigm to improve the computational efficiency of deep neural networks by constructing multiple classifiers to let easy samples exit at shallow layers while avoiding redundant computa...
Deep Learning Human Activities Signal Processing, Computer-Assisted Humans Machine Learning Wearable Electronic Devices Neural Networks, Computer Algorithms
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ISGAN: Unsupervised Domain Adaptation With Improved Symmetric GAN for Cross-Modality Multi-Organ Segmentation.

IEEE journal of biomedical and health informatics Jun 1, 2025
The differences between cross-modality medical images are significant, so several studies are working on unsupervised domain adaptation (UDA) segmentation, which aims to adapt a segmentation model trained on a labeled source domain to an unlabeled ta...
Databases, Factual Image Processing, Computer-Assisted Humans Neural Networks, Computer Abdomen Unsupervised Machine Learning Heart Algorithms Magnetic Resonance Imaging
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Explicit Abnormality Extraction for Unsupervised Motion Artifact Reduction in Magnetic Resonance Imaging.

IEEE journal of biomedical and health informatics Jun 1, 2025
Motion artifacts compromise the quality of magnetic resonance imaging (MRI) and pose challenges to achieving diagnostic outcomes and image-guided therapies. In recent years, supervised deep learning approaches have emerged as successful solutions for...
Unsupervised Machine Learning Humans Motion Image Processing, Computer-Assisted Artifacts Algorithms Magnetic Resonance Imaging Brain
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