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Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.
Scientific reports
Apr 7, 2025
Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder (ASD). ASD is typically detected using a case-finding approach based on symptoms and family history,...
Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and computed tomography angiography (CTA) is essential in providing supportive information for diagnosing and treatment planning of multiple intracranial vascul...
Multi-Scale Dynamic Sparse Token Multi-Instance Learning for Pathology Image Classification.
IEEE journal of biomedical and health informatics
Apr 4, 2025
In many challenging breast cancer pathology images, the proportion of truly informative tumor regions is extremely limited. The disparity between the essential information required for clinical diagnosis (Tumor area less than 10$\%$) and the vast amo...
Aceso-DSAL: Discovering Clinical Evidences From Medical Literature Based on Distant Supervision and Active Learning.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Automatic extraction of valuable, structured evidence from the exponentially growing clinical trial literature can help physicians practice evidence-based medicine quickly and accurately. However, current research on evidence extraction has been limi...
Label-Free Medical Image Quality Evaluation by Semantics-Aware Contrastive Learning in IoMT.
IEEE journal of biomedical and health informatics
Apr 4, 2025
With the rapid development of the Internet-of-Medical-Things (IoMT) in recent years, it has emerged as a promising solution to alleviate the workload of medical staff, particularly in the field of Medical Image Quality Assessment (MIQA). By deploying...
Asymmetric Adaptive Heterogeneous Network for Multi-Modality Medical Image Segmentation.
IEEE transactions on medical imaging
Apr 3, 2025
Existing studies of multi-modality medical image segmentation tend to aggregate all modalities without discrimination and employ multiple symmetric encoders or decoders for feature extraction and fusion. They often overlook the different contribution...
Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation.
IEEE transactions on medical imaging
Apr 3, 2025
Anatomical abnormality detection and report generation of chest X-ray (CXR) are two essential tasks in clinical practice. The former aims at localizing and characterizing cardiopulmonary radiological findings in CXRs, while the latter summarizes the ...
HisynSeg: Weakly-Supervised Histopathological Image Segmentation via Image-Mixing Synthesis and Consistency Regularization.
IEEE transactions on medical imaging
Apr 3, 2025
Tissue semantic segmentation is one of the key tasks in computational pathology. To avoid the expensive and laborious acquisition of pixel-level annotations, a wide range of studies attempt to adopt the class activation map (CAM), a weakly-supervised...
MT-CooL: Multi-Task Cooperative Learning via Flat Minima Searching.
IEEE transactions on medical imaging
Apr 3, 2025
While multi-task learning (MTL) has been widely developed for natural image analysis, its potential for enhancing performance in medical imaging remains relatively unexplored. Most methods formulate MTL as a multi-objective problem, inherently forcin...
Identifying progression subphenotypes of Alzheimer's disease from large-scale electronic health records with machine learning.
Journal of biomedical informatics
Apr 1, 2025
OBJECTIVE: Identification of clinically meaningful subphenotypes of disease progression can enhance the understanding of disease heterogeneity and underlying pathophysiology. In this study, we propose a machine learning framework to identify subpheno...
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