AIMC Topic: Deep Learning
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Realistic fundus photograph generation for improving automated disease classification.
The British journal of ophthalmology
Jun 23, 2025
AIMS: This study aims to investigate whether denoising diffusion probabilistic models (DDPMs) could generate realistic retinal images, and if they could be used to improve the performance of a deep convolutional neural network (CNN) ensemble for mult...
High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS.
PloS one
Jun 23, 2025
To address the complex deformation of wellbores influenced by surrounding coal mining operations, this study employed an improved modified least-squares ambiguity decorrelation (MLAMBDA) algorithm based on the double-difference model for high-frequen...
Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.
European radiology experimental
Jun 19, 2025
BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (RPE), which is a prognostic imaging biomarker for a severe course of illness. This study aimed to develop a deep learning-based algorithm for the auto...
Deep generative models for Bayesian inference on high-rate sensor data: applications in automotive radar and medical imaging.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 19, 2025
Deep generative models (DGMs) have been studied and developed primarily in the context of natural images and computer vision. This has spurred the development of (Bayesian) methods that use these generative models for inverse problems in image restor...
Deep learning for differential diagnosis of parotid tumors based on 2.5D magnetic resonance imaging.
Annals of medicine
Jun 18, 2025
PURPOSE: Accurate preoperative diagnosis of parotid gland tumors (PGTs) is crucial for surgical planning since malignant tumors require more extensive excision. Though fine-needle aspiration biopsy is the diagnostic gold standard, its sensitivity in ...
Smartphone eye-tracking with deep learning: Data quality and field testing.
Behavior research methods
Jun 18, 2025
Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial intelligence and mobile computing, deep learning algorithms for computer vision-based eye tracking ha...
Advancing breast cancer prediction: Comparative analysis of ML models and deep learning-based multi-model ensembles on original and synthetic datasets.
PloS one
Jun 18, 2025
Breast cancer is a significant global health concern with rising incidence and mortality rates. Current diagnostic methods face challenges, necessitating improved approaches. This study employs various machine learning (ML) algorithms, including KNN,...
Study on the quantitative analysis of Tilianin based on Raman spectroscopy combined with deep learning.
PloS one
Jun 18, 2025
Tilianin is a commonly used pharmaceutical ingredient with various biological activities such as antioxidant, anti-inflammatory, and anticancer, which is able to exert antitumor effects by inhibiting tumor cell proliferation, inducing apoptosis and i...
DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.
PloS one
Jun 18, 2025
As one of the most critical post-replication modifications, N6-methylation (6mA) at adenine residue plays an important role in a variety of biological functions. Existing computational methods for identifying 6mA sites across large genomic regions te...
Research on learning achievement classification based on machine learning.
PloS one
Jun 18, 2025
Academic achievement is an important index to measure the quality of education and students' learning outcomes. Reasonable and accurate prediction of academic achievement can help improve teachers' educational methods. And it also provides correspond...
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