AIMC Topic: Neural Networks, Computer

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Optimizing MRI sequence classification performance: insights from domain shift analysis.

European radiology
BACKGROUND: MRI sequence classification becomes challenging in multicenter studies due to variability in imaging protocols, leading to unreliable metadata and requiring labor-intensive manual annotation. While numerous automated MRI sequence identifi...

Evaluating the generalizability of video-based assessment of intraoperative surgical skill in capsulorhexis.

International journal of computer assisted radiology and surgery
PURPOSE: Assessment of intraoperative surgical skill is necessary to train surgeons and certify them for practice. The generalizability of deep learning models for video-based assessment (VBA) of surgical skill has not yet been evaluated. In this wor...

nnU-Net-based high-resolution CT features quantification for interstitial lung diseases.

European radiology
OBJECTIVES: To develop a new high-resolution (HR)CT abnormalities quantification tool (CVILDES) for interstitial lung diseases (ILDs) based on the nnU-Net network structure and to determine whether the quantitative parameters derived from this new so...

Volumetric Medical Image Segmentation Through Dual Self-Distillation in U-Shaped Networks.

IEEE transactions on bio-medical engineering
U-shaped networks and its variants have demonstrated exceptional results for medical image segmentation. In this paper, we propose a novel dual self-distillation (DSD) framework in U-shaped networks for volumetric medical image segmentation. DSD dist...

Hierarchical Dynamic Graph Convolutional Network With Interpretability for EEG-Based Emotion Recognition.

IEEE transactions on neural networks and learning systems
Graph convolutional networks (GCNs) have shown great prowess in learning topological relationships among electroencephalogram (EEG) channels for EEG-based emotion recognition. However, most existing GCN-only methods are designed with a single spatial...

Machine learning prediction of thrombolysis efficacy using hs-CRP and inflammatory markers in stroke.

Medicine
The aim of this study was to investigate the relationship between serum ultrasensitive C-reactive protein (hs-CRP) levels and stroke incidence and to assess its potential role in decision-making for thrombolytic therapy in stroke. Given that hs-CRP i...

Cardiac amyloidosis detection from a single echocardiographic video clip: a novel artificial intelligence-based screening tool.

European heart journal
BACKGROUND AND AIMS: Accurate differentiation of cardiac amyloidosis (CA) from phenotypic mimics remains challenging using current clinical and echocardiographic techniques. The accuracy of a novel artificial intelligence (AI) screening algorithm for...

Early diagnosis model of mycosis fungoides and five inflammatory skin diseases based on a multimodal data-based convolutional neural network.

The British journal of dermatology
BACKGROUND: Mycosis fungoides (MF) is the most common type of cutaneous T-cell lymphoma, and early-stage MF is difficult to differentiate from erythematous inflammatory disease. With the exception of biopsy, noninvasive information such as a patient'...

Benchtop Vis-NIR spectroscopy meets machine learning for multi-task analysis in Hongmeiren citrus: Geographical origin identification and antioxidant component quantification.

Food chemistry
Due to geographical indication advantage of Hongmeiren (HMR) citrus, economically motivated origin fraud has emerged, alongside significant differences in antioxidant components. This study employed benchtop visible and near-infrared (Vis-NIR) spectr...

Detection and classification of meat freshness using an optimized deep learning method.

Food chemistry
Accurate assessment of meat freshness is critical for ensuring food safety, reducing waste, and maintaining quality control in the food industry. Efficient classification of meat into categories such as fresh, half-fresh, and spoiled is essential for...