AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 701 to 710 of 1118 articles

3D Context-Aware Convolutional Neural Network for False Positive Reduction in Clustered Microcalcifications Detection.

IEEE journal of biomedical and health informatics Mar 5, 2021
False positives (FPs) reduction is indispensable for clustered microcalcifications (MCs) detection in digital breast tomosynthesis (DBT), since there might be excessive false candidates in the detection stage. Considering that DBT volume has an aniso...
Humans Neural Networks, Computer Algorithms Female Calcinosis Mammography
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Deep Anatomical Context Feature Learning for Cephalometric Landmark Detection.

IEEE journal of biomedical and health informatics Mar 5, 2021
In the past decade, anatomical context features have been widely used for cephalometric landmark detection and significant progress is still being made. However, most existing methods rely on handcrafted graphical models rather than incorporating ana...
Humans Neural Networks, Computer Radiography Cephalometry
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Deep Matrix Factorization Improves Prediction of Human CircRNA-Disease Associations.

IEEE journal of biomedical and health informatics Mar 5, 2021
In recent years, more and more evidence indicates that circular RNAs (circRNAs) with covalently closed loop play various roles in biological processes. Dysregulation and mutation of circRNAs may be implicated in diseases. Due to its stable structure ...
Humans Neural Networks, Computer Forecasting Research Design RNA, Circular
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Disease Prediction via Graph Neural Networks.

IEEE journal of biomedical and health informatics Mar 5, 2021
With the increasingly available electronic medical records (EMRs), disease prediction has recently gained immense research attention, where an accurate classifier needs to be trained to map the input prediction signals (e.g., symptoms, patient demogr...
Humans Neural Networks, Computer Machine Learning Electronic Health Records Female
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COVID-19 CT Image Synthesis With a Conditional Generative Adversarial Network.

IEEE journal of biomedical and health informatics Feb 5, 2021
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread rapidly since December 2019. Real-time reverse transcription polymerase chain reaction (rRT-PCR) and chest computed tomography (CT) imaging both play an important role ...
Humans COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Lung Deep Learning Radiography, Thoracic
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Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019.

IEEE journal of biomedical and health informatics Feb 5, 2021
Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different c...
Humans Diagnosis, Computer-Assisted Deep Learning Lung Neoplasms
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Measuring Domain Shift for Deep Learning in Histopathology.

IEEE journal of biomedical and health informatics Feb 5, 2021
The high capacity of neural networks allows fitting models to data with high precision, but makes generalization to unseen data a challenge. If a domain shift exists, i.e. differences in image statistics between training and test data, care needs to ...
Humans Neural Networks, Computer Deep Learning
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Attention-Guided Multi-Branch Convolutional Neural Network for Mitosis Detection From Histopathological Images.

IEEE journal of biomedical and health informatics Feb 5, 2021
Mitotic count is an important indicator for assessing the invasiveness of breast cancers. Currently, the number of mitoses is manually counted by pathologists, which is both tedious and time-consuming. To address this situation, we propose a fast and...
Humans Neural Networks, Computer Female Breast Neoplasms Attention Mitosis
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Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract.

IEEE journal of biomedical and health informatics Feb 5, 2021
Accurate lesion segmentation based on endoscopy images is a fundamental task for the automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually use hand-crafted features for representing endoscopy images, while featur...
Humans Neural Networks, Computer Endoscopy Image Processing, Computer-Assisted Gastrointestinal Tract
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Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images.

IEEE journal of biomedical and health informatics Feb 5, 2021
With the increasing amount of image data collected from biomedical experiments there is an urgent need for smarter and more effective analysis methods. Many scientific questions require analysis of image sub-regions related to some specific biology. ...
Humans Deep Learning Image Processing, Computer-Assisted Semantics
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