AIMC Topic: Deep Learning
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Development and validation of a deep learning algorithm for prediction of pediatric recurrent intussusception in ultrasound images and radiographs.
BMC medical imaging
Mar 3, 2025
PURPOSES: To develop a predictive model for recurrent intussusception based on abdominal ultrasound (US) images and abdominal radiographs.
An intelligent framework for skin cancer detection and classification using fusion of Squeeze-Excitation-DenseNet with Metaheuristic-driven ensemble deep learning models.
Scientific reports
Mar 3, 2025
Skin cancer is the most dominant and critical method of cancer, which arises all over the world. Its damaging effects can range from disfigurement to major medical expenditures and even death if not analyzed and preserved timely. Conventional models ...
Quantitative analysis and evaluation of winter and summer landscape colors in the Yangzhou ancient Canal utilizing deep learning.
Scientific reports
Mar 3, 2025
Color is an important index for human visual evaluation of landscape, and it is also a key factor affecting people's recognition and experience of heritage landscape. In this study, five important sites of the Yangzhou Grand Canal were selected for t...
Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.
Scientific reports
Mar 3, 2025
Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...
Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification.
Scientific reports
Mar 3, 2025
Current breast cancer diagnosis methods often face limitations such as high cost, time consumption, and inter-observer variability. To address these challenges, this research proposes a novel deep learning framework that leverages generative adversar...
Modifying the severity and appearance of psoriasis using deep learning to simulate anticipated improvements during treatment.
Scientific reports
Mar 3, 2025
A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, after being trained on 375 photographs of patients with psoriasis taken in a clinical setting. A latent w-space vector was identified that allowed the...
Emotion-RGC net: A novel approach for emotion recognition in social media using RoBERTa and Graph Neural Networks.
PloS one
Mar 3, 2025
Emotion recognition in social media is a challenging task due to the complex and unstructured nature of user-generated content. In this paper, we propose Emotion-RGC Net, a novel deep learning model that integrates RoBERTa, Graph Neural Networks (GNN...
Development of a deep learning radiomics model combining lumbar CT, multi-sequence MRI, and clinical data to predict high-risk cage subsidence after lumbar fusion: a retrospective multicenter study.
Biomedical engineering online
Mar 2, 2025
BACKGROUND: To develop and validate a model that integrates clinical data, deep learning radiomics, and radiomic features to predict high-risk patients for cage subsidence (CS) after lumbar fusion.
Deep learning for tibial plateau fracture detection and classification.
The Knee
Mar 1, 2025
BACKGROUND: Deep learning (DL) has been shown to be successful in interpreting radiographs and aiding in fracture detection and classification. However, no study has aimed to develop a computer vision model for tibia plateau fractures using the Schat...
Geometric and Dosimetric Evaluation of a RayStation Deep Learning Model for Auto-Segmentation of Organs at Risk in a Real-World Head and Neck Cancer Dataset.
Clinical oncology (Royal College of Radiologists (Great Britain))
Mar 1, 2025
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).
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