AIMC Journal:
IEEE journal of biomedical and health informatics

Showing 541 to 550 of 1110 articles

Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion.

IEEE journal of biomedical and health informatics
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image; and the transformed atlas labels can be combi...

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure.

IEEE journal of biomedical and health informatics
Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health records may improve prediction but remain unexplainable hampering their wider use in medical practice....

Unsupervised Gait Phase Estimation With Domain-Adversarial Neural Network and Adaptive Window.

IEEE journal of biomedical and health informatics
The performanceof previous machine learning models for gait phase is only satisfactory under limited conditions. First, they produce accurate estimations only when the ground truth of the gait phase (of the target subject) is known. In contrast, when...

Multi-Level Functional Connectivity Fusion Classification Framework for Brain Disease Diagnosis.

IEEE journal of biomedical and health informatics
Brain disease diagnosis is a new hotspot in the cross research of artificial intelligence and neuroscience. Quantitative analysis of functional magnetic resonance imaging (fMRI) data can provide valuable biomarkers that contributes to clinical diagno...

Personalized On-Device E-Health Analytics With Decentralized Block Coordinate Descent.

IEEE journal of biomedical and health informatics
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating. Nowadays, enhancement on medical diagnosis via machine learning models has been highly effective in many aspects of e-health analy...

Uncertainty-Aware Deep Learning With Cross-Task Supervision for PHE Segmentation on CT Images.

IEEE journal of biomedical and health informatics
Perihematomal edema (PHE) volume, surrounding spontaneous intracerebral hemorrhage (SICH), is an important biomarker for the presence of SICH-associated diseases. However, due to irregular shapes and extremely low contrast of PHE on CT images, manual...

AL-Net: Attention Learning Network Based on Multi-Task Learning for Cervical Nucleus Segmentation.

IEEE journal of biomedical and health informatics
Cervical nucleus segmentation is a crucial and challenging issue in automatic pathological diagnosis due to uneven staining, blurry boundaries, and adherent or overlapping nuclei in nucleus images. To overcome the limitation of current methods, we pr...

Unsupervised Cross-Modality Domain Adaptation Network for X-Ray to CT Registration.

IEEE journal of biomedical and health informatics
2D/3D registration that achieves high accuracy and real-time computation is one of the enabling technologies for radiotherapy and image-guided surgeries. Recently, the Convolutional Neural Network (CNN) has been explored to significantly improve the ...

Review of Artificial Intelligence Techniques in Chronic Obstructive Lung Disease.

IEEE journal of biomedical and health informatics
BACKGROUND: Artificial Intelligence (AI) has proven to be an invaluable asset in the healthcare domain, where massive amounts of data are produced. Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous chronic condition with multiscale mani...

Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning.

IEEE journal of biomedical and health informatics
Due to the COVID-19 pandemic, vaccine development and community vaccination studies are carried out all over the world. At this stage, the opposition to the vaccine seen in the society or the lack of trust in the developed vaccine is an important fac...