AIMC Topic: Deep Learning

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Predicting Drug-miRNA Associations Combining SDNE with BiGRU.

IEEE journal of biomedical and health informatics May 6, 2025
It is well recognized that abnormal miRNA expression can result in drug resistance and pose a challenge to miRNA-based treatments. However, the drug-miRNA associations (DMA) are still incompletely understood. Conventional biological experiments have ...
MicroRNAs Deep Learning Pharmaceutical Preparations Computational Biology Humans Algorithms
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FlexibleSleepNet:A Model for Automatic Sleep Stage Classification Based on Multi-Channel Polysomnography.

IEEE journal of biomedical and health informatics May 6, 2025
In the task of automatic sleep stage classification, deep learning models often face the challenge of balancing temporal-spatial feature extraction with computational complexity. To address this issue, this study introduces FlexibleSleepNet, a lightw...
Signal Processing, Computer-Assisted Polysomnography Sleep Stages Adult Deep Learning Neural Networks, Computer Databases, Factual Humans
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SWMA-UNet: Multi-Path Attention Network for Improved Medical Image Segmentation.

IEEE journal of biomedical and health informatics May 6, 2025
In recent years, deep learning achieves significant advancements in medical image segmentation. Research finds that integrating Transformers and CNNs effectively addresses the limitations of CNNs in managing long-distance dependencies and understandi...
Image Processing, Computer-Assisted Algorithms Databases, Factual Deep Learning Humans Neural Networks, Computer
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Frozen Large-Scale Pretrained Vision-Language Models are the Effective Foundational Backbone for Multimodal Breast Cancer Prediction.

IEEE journal of biomedical and health informatics May 6, 2025
Breast cancer is a pervasive global health concern among women. Leveraging multimodal data from enterprise patient databases-including Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHRs)-holds promise for improving...
Female Breast Neoplasms Mammography Deep Learning Databases, Factual Electronic Health Records Humans
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Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma From Multi-Sequence Magnetic Resonance Imaging Based on Deep Fusion Representation Learning.

IEEE journal of biomedical and health informatics May 6, 2025
Recent studies have identified microvascular invasion (MVI) as the most vital independent biomarker associated with early tumor recurrence. With advancements in medical technology, several computational methods have been developed to predict preopera...
Microvessels Liver Image Interpretation, Computer-Assisted Humans Deep Learning Adult Female Male Aged Middle Aged Carcinoma, Hepatocellular Magnetic Resonance Imaging Neoplasm Invasiveness Liver Neoplasms
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MACTFusion: Lightweight Cross Transformer for Adaptive Multimodal Medical Image Fusion.

IEEE journal of biomedical and health informatics May 6, 2025
Multimodal medical image fusion aims to integrate complementary information from different modalities of medical images. Deep learning methods, especially recent vision Transformers, have effectively improved image fusion performance. However, there ...
Algorithms Brain Image Processing, Computer-Assisted Multimodal Imaging Deep Learning Humans
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A Lesion-Fusion Neural Network for Multi-View Diabetic Retinopathy Grading.

IEEE journal of biomedical and health informatics May 6, 2025
As the most common complication of diabetes, diabetic retinopathy (DR) is one of the main causes of irreversible blindness. Automatic DR grading plays a crucial role in early diagnosis and intervention, reducing the risk of vision loss in people with...
Neural Networks, Computer Algorithms Deep Learning Humans Diabetic Retinopathy Image Interpretation, Computer-Assisted Fundus Oculi Retina
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Adaptive Cross-Feature Fusion Network With Inconsistency Guidance for Multi-Modal Brain Tumor Segmentation.

IEEE journal of biomedical and health informatics May 6, 2025
In the context of contemporary artificial intelligence, increasing deep learning (DL) based segmentation methods have been recently proposed for brain tumor segmentation (BraTS) via analysis of multi-modal MRI. However, known DL-based works usually d...
Humans Neural Networks, Computer Multimodal Imaging Image Interpretation, Computer-Assisted Brain Neoplasms Deep Learning Algorithms Magnetic Resonance Imaging Brain
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PEARL: Cascaded Self-Supervised Cross-Fusion Learning for Parallel MRI Acceleration.

IEEE journal of biomedical and health informatics May 6, 2025
Supervised deep learning (SDL) methodology holds promise for accelerated magnetic resonance imaging (AMRI) but is hampered by the reliance on extensive training data. Some self-supervised frameworks, such as deep image prior (DIP), have emerged, elim...
Algorithms Magnetic Resonance Imaging Supervised Machine Learning Brain Deep Learning Humans Image Processing, Computer-Assisted
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iEnhancer-DS: Attention-based improved densenet for identifying enhancers and their strength.

Computational biology and chemistry May 5, 2025
Enhancers are short DNA fragments that enhance gene expression by binding to transcription factors. Accurately identifying enhancers and their strength is crucial for understanding gene regulation mechanisms. However, traditional enhancer sequencing ...
Deep Learning Sequence Analysis, DNA DNA Enhancer Elements, Genetic Convolutional Neural Networks Computational Biology
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