AIMC Topic: Deep Learning
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Deep learning approach based on a patch residual for pediatric supracondylar subtle fracture detection.
Biomolecules & biomedicine
May 8, 2025
Supracondylar humerus fractures in children are among the most common elbow fractures in pediatrics. However, their diagnosis can be particularly challenging due to the anatomical characteristics and imaging features of the pediatric skeleton. In rec...
Deep learning segmentation of periarterial and perivenous capillary-free zones in optical coherence tomography angiography.
Journal of biomedical optics
May 8, 2025
SIGNIFICANCE: Automated segmentation of periarterial and perivenous capillary-free zones (CFZs) in optical coherence tomography angiography (OCTA) can significantly improve early detection and monitoring of diabetic retinopathy (DR), a leading cause ...
Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.
Nature methods
May 8, 2025
Subcellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with unprecedented precision. However, the agnostic and a...
AI-driven glomerular morphology quantification: a novel pipeline for assessing basement membrane thickness and podocyte foot process effacement in kidney diseases.
Computer methods and programs in biomedicine
May 7, 2025
BACKGROUND AND OBJECTIVE: Measuring the thickness of the glomerular basement membrane (GBM) and assessing the percentage of podocyte foot process effacement (%PFPE) are important for diagnosing non-neoplastic kidney diseases. However, when performed ...
Light-microscopy-based connectomic reconstruction of mammalian brain tissue.
Nature
May 7, 2025
The information-processing capability of the brain's cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can b...
Detection of Negative Emotions in Short Texts Using Deep Neural Networks.
Cyberpsychology, behavior and social networking
May 7, 2025
Emotion detection is crucial in various domains, including psychology, health, social sciences, and marketing. Specifically, in psychology, identifying negative emotions in short Spanish texts, such as tweets, is vital for understanding individuals' ...
Deep learning approaches for classification tasks in medical X-ray, MRI, and ultrasound images: a scoping review.
BMC medical imaging
May 7, 2025
Medical images occupy the largest part of the existing medical information and dealing with them is challenging not only in terms of management but also in terms of interpretation and analysis. Hence, analyzing, understanding, and classifying them, b...
Sculpting molecules in text-3D space: a flexible substructure aware framework for text-oriented molecular optimization.
BMC bioinformatics
May 7, 2025
The integration of deep learning, particularly AI-Generated Content, with high-quality data derived from ab initio calculations has emerged as a promising avenue for transforming the landscape of scientific research. However, the challenge of designi...
A deep learning model combining circulating tumor cells and radiological features in the multi-classification of mediastinal lesions in comparison with thoracic surgeons: a large-scale retrospective study.
BMC medicine
May 7, 2025
BACKGROUND: CT images and circulating tumor cells (CTCs) are indispensable for diagnosing the mediastinal lesions by providing radiological and intra-tumoral information. This study aimed to develop and validate a deep multimodal fusion network (DMFN...
Enhanced classification of tinnitus patients using EEG microstates and deep learning techniques.
Scientific reports
May 7, 2025
This study aims to deepen the understanding and classification of tinnitus through a comprehensive analysis of EEG signals utilizing innovative microstate analysis techniques and cutting-edge machine learning approaches. EEG data were collected from ...
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