AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 621 to 630 of 1116 articles

ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.

IEEE journal of biomedical and health informatics Oct 5, 2021
Due to the complexity of myocardial infarction (MI) waveform, most traditional automatic diagnosis models rarely detect it, while those able to detect MI often require high computing and storage capacity, rendering them unsuitable for portable device...
Humans Databases, Factual Electrocardiography Algorithms Neural Networks, Computer Myocardial Infarction
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DSAL: Deeply Supervised Active Learning From Strong and Weak Labelers for Biomedical Image Segmentation.

IEEE journal of biomedical and health informatics Oct 5, 2021
Image segmentation is one of the most essential biomedical image processing problems for different imaging modalities, including microscopy and X-ray in the Internet-of-Medical-Things (IoMT) domain. However, annotating biomedical images is knowledge-...
Isoquinolines Humans Image Processing, Computer-Assisted Supervised Machine Learning
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Distant Domain Transfer Learning for Medical Imaging.

IEEE journal of biomedical and health informatics Oct 5, 2021
Medical image processing is one of the most important topics in the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-art performances on medical imaging tasks. In this paper, we propose a novel transfer...
COVID-19 Tomography, X-Ray Computed Machine Learning Humans
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A Deep Learning Approach for Colonoscopy Pathology WSI Analysis: Accurate Segmentation and Classification.

IEEE journal of biomedical and health informatics Oct 5, 2021
Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy pathology examination can identify cells of early-stage colon tumors in small tissue image slices. But, such examination is time-consuming and exhausting on high re...
Deep Learning Image Processing, Computer-Assisted Colonoscopy Neural Networks, Computer
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DMC-Fusion: Deep Multi-Cascade Fusion With Classifier-Based Feature Synthesis for Medical Multi-Modal Images.

IEEE journal of biomedical and health informatics Sep 3, 2021
Multi-modal medical image fusion is a challenging yet important task for precision diagnosis and surgical planning in clinical practice. Although single feature fusion strategy such as Densefuse has achieved inspiring performance, it tends to be not ...
Normal Distribution Brain Neural Networks, Computer Signal-To-Noise Ratio
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Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.

IEEE journal of biomedical and health informatics Sep 3, 2021
With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, the deep learning-based detections for some common eye dise...
Algorithms Neural Networks, Computer Fundus Oculi Humans ROC Curve Deep Learning Glaucoma
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Method of Tumor Pathological Micronecrosis Quantification Via Deep Learning From Label Fuzzy Proportions.

IEEE journal of biomedical and health informatics Sep 3, 2021
The presence of necrosis is associated with tumor progression and patient outcomes in many cancers, but existing analyses rarely adopt quantitative methods because the manual quantification of histopathological features is too expensive. We aim to ac...
Liver Neoplasms Image Processing, Computer-Assisted Deep Learning Humans
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Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms.

IEEE journal of biomedical and health informatics Sep 3, 2021
Current clinical practice or radiomics studies of pancreatic neuroendocrine neoplasms (pNENs) require manual delineation of the lesions in computed tomography (CT) images, which is time-consuming and subjective. We used a semi-automatic deep learning...
Humans Tomography, X-Ray Computed Retrospective Studies Area Under Curve Deep Learning ROC Curve Neoplasms
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rBPDL:Predicting RNA-Binding Proteins Using Deep Learning.

IEEE journal of biomedical and health informatics Sep 3, 2021
RNA-binding protein (RBP) is a powerful and wide-ranging regulator that plays an important role in cell development, differentiation, metabolism, health and disease. The prediction of RBPs provides valuable guidance for biologists. Although experimen...
Binding Sites RNA-Binding Proteins Neural Networks, Computer Protein Binding Deep Learning
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A Combinatorial Deep Learning Structure for Precise Depth of Anesthesia Estimation From EEG Signals.

IEEE journal of biomedical and health informatics Sep 3, 2021
Electroencephalography (EEG) is commonly used to measure the depth of anesthesia (DOA) because EEG reflects surgical pain and state of the brain. However, precise and real-time estimation of DOA index for painful surgical operations is challenging du...
Anesthesia Electroencephalography Neural Networks, Computer Deep Learning Algorithms Humans
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