AIMC Topic: Deep Learning

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Enhanced HER-2 prediction in breast cancer through synergistic integration of deep learning, ultrasound radiomics, and clinical data.

Scientific reports Jul 24, 2025
This study integrates ultrasound Radiomics with clinical data to enhance the diagnostic accuracy of HER-2 expression status in breast cancer, aiming to provide more reliable treatment strategies for this aggressive disease. We included ultrasound ima...
Ultrasonography Ultrasonography, Mammary Receptor, ErbB-2 Middle Aged Humans Deep Learning Adult Breast Neoplasms Radiomics Female Aged
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Hybrid deep learning framework based on EfficientViT for classification of gastrointestinal diseases.

Scientific reports Jul 24, 2025
GI diseases are one of the leading causes of morbidity and mortality worldwide, and early and accurate diagnosis is considered to be very important. Traditional methods like endoscopy take time and depend majorly on the judgment of the physician. The...
Humans Algorithms Image Processing, Computer-Assisted Gastrointestinal Diseases Deep Learning
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A Multi-Modal Pelvic MRI Dataset for Deep Learning-Based Pelvic Organ Segmentation in Endometriosis.

Scientific data Jul 24, 2025
Endometriosis affects approximately 190 million females of reproductive age worldwide. Magnetic Resonance Imaging (MRI) has been recommended as the primary non-invasive diagnostic method for endometriosis. This study presents new female pelvic MRI mu...
Endometriosis Ovary Deep Learning Magnetic Resonance Imaging Pelvis Humans Female
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Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

Nature communications Jul 24, 2025
The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in d...
Protein Aggregation, Pathological Protein Folding Huntington Disease Kinetics Microscopy Microscopy, Fluorescence Protein Aggregates Neurodegenerative Diseases Neural Networks, Computer Deep Learning Humans
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Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study.

Journal of medical Internet research Jul 24, 2025
BACKGROUND: Incorporating initial serum chloride levels as a prognostic indicator in the intensive care environment has the potential to refine risk stratification and tailor treatment strategies, leading to more efficient use of clinical resources a...
Aged Male Middle Aged Intensive Care Units Female Cohort Studies Hospital Mortality Chlorides Deep Learning China Humans Prognosis
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An automated hybrid deep learning framework for paddy leaf disease identification and classification.

Scientific reports Jul 24, 2025
In India, agriculture remains the primary source of livelihood for many people. Pathogen attacks in crops and plants significantly diminish both the yield and quality of production, leading to financial losses. As a result, identifying diseases in cr...
Crops, Agricultural Deep Learning Plant Leaves Plant Diseases Algorithms Image Processing, Computer-Assisted Oryza
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FedGAN: Federated diabetic retinopathy image generation.

PloS one Jul 24, 2025
Deep learning models for diagnostic applications require large amounts of sensitive patient data, raising privacy concerns under centralized training paradigms. We propose FedGAN, a federated learning framework for synthetic medical image generation ...
Image Processing, Computer-Assisted Algorithms Humans Tomography, X-Ray Computed Deep Learning Diabetic Retinopathy
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Multi-modal deep learning for intelligent landscape design generation: A novel CBS3-LandGen model.

PloS one Jul 24, 2025
With the acceleration of the global urbanization process, landscape design is facing increasingly complex challenges. Traditional manual design methods are gradually unable to meet the needs for efficiency, precision, and sustainability. To address t...
Urbanization Humans Models, Theoretical Conservation of Natural Resources Deep Learning
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Deep learning for pediatric chest x-ray diagnosis: Repurposing a commercial tool developed for adults.

PloS one Jul 24, 2025
The number of commercially available artificial intelligence (AI) tools to support radiological workflows is constantly increasing, yet dedicated solutions for children are largely unavailable. Here, we repurposed an AI-tool developed for chest radio...
Female Adult Male Humans Child Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Adolescent Child, Preschool Deep Learning
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A hybrid model for detecting motion artifacts in ballistocardiogram signals.

Biomedical engineering online Jul 23, 2025
BACKGROUND: The field of contactless health monitoring has witnessed significant advancements with the advent of piezoelectric sensing technology, which enables the monitoring of vital signs such as heart rate and respiration without requiring direct...
Movement Ballistocardiography Humans Signal Processing, Computer-Assisted Motion Deep Learning Artifacts
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