AIMC Topic: Deep Learning
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Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval.
Scientific reports
Mar 14, 2025
Evidence-based medicine is the preferred procedure among clinicians for treating patients. Content-based medical image retrieval (CBMIR) is widely used to extract evidence from a large archive of medical images. Developing effective CBMIR systems for...
Comparative analysis of deep learning architectures for breast region segmentation with a novel breast boundary proposal.
Scientific reports
Mar 14, 2025
Segmentation of the breast region in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for the automatic measurement of breast density and the quantitative analysis of imaging findings. This study aims to compare various dee...
Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation.
Scientific reports
Mar 14, 2025
Accurately extracting lesions from medical images is a fundamental but challenging problem in medical image analysis. In recent years, methods based on convolutional neural networks and Transformer have achieved great success in the medical image seg...
Deep learning-based classification of hemiplegia and diplegia in cerebral palsy using postural control analysis.
Scientific reports
Mar 14, 2025
Cerebral palsy (CP) is a neurological condition that affects mobility and motor control, presenting significant challenges for accurate diagnosis, particularly in cases of hemiplegia and diplegia. This study proposes a method of classification utiliz...
Deep learning prioritizes cancer mutations that alter protein nucleocytoplasmic shuttling to drive tumorigenesis.
Nature communications
Mar 14, 2025
Genetic variants can affect protein function by driving aberrant subcellular localization. However, comprehensive analysis of how mutations promote tumor progression by influencing nuclear localization is currently lacking. Here, we systematically ch...
Deep representation learning for clustering longitudinal survival data from electronic health records.
Nature communications
Mar 14, 2025
Precision medicine requires accurate identification of clinically relevant patient subgroups. Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subgroups. However, many existing ...
Automatic Detection of Cognitive Impairment in Patients With White Matter Hyperintensity Using Deep Learning and Radiomics.
American journal of Alzheimer's disease and other dementias
Mar 14, 2025
White matter hyperintensity (WMH) is associated with cognitive impairment. In this study, 79 patients with WMH from hospital 1 were randomly divided into a training set (62 patients) and an internal validation set (17 patients). In addition, 29 WMH p...
Deep learning for the prediction of acute kidney injury after coronary angiography and intervention in patients with chronic kidney disease: a model development and validation study.
Renal failure
Mar 13, 2025
BACKGROUND: Patients with chronic kidney disease (CKD) are considered the primary population at risk for post-contrast acute kidney injury (PC-AKI), yet there are few predictive tools specifically designed for this vulnerable population.
CQENet: A segmentation model for nasopharyngeal carcinoma based on confidence quantitative evaluation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 13, 2025
Accurate segmentation of the tumor regions of nasopharyngeal carcinoma (NPC) is of significant importance for radiotherapy of NPC. However, the precision of existing automatic segmentation methods for NPC remains inadequate, primarily manifested in t...
Exploring the significance of the frontal lobe for diagnosis of schizophrenia using explainable artificial intelligence and group level analysis.
Psychiatry research. Neuroimaging
Mar 13, 2025
Schizophrenia (SZ) is a complex mental disorder characterized by a profound disruption in cognition and emotion, often resulting in a distorted perception of reality. Magnetic resonance imaging (MRI) is an essential tool for diagnosing SZ which helps...
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