AIMC Topic: Deep Learning
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Quantitative Ischemic Lesions of Portable Low-Field Strength MRI Using Deep Learning-Based Super-Resolution.
Stroke
Apr 16, 2025
BACKGROUND: Deep learning-based synthetic super-resolution magnetic resonance imaging (SynthMRI) may improve the quantitative lesion performance of portable low-field strength magnetic resonance imaging (LF-MRI). The aim of this study is to evaluate ...
Developing a novel Temporal Air-quality Risk Index using LSTM autoencoder: A case study with South Korean air quality data.
The Science of the total environment
Apr 16, 2025
As public awareness of environmental and health issues grows, providing accurate and accessible environmental risk information is essential for informed decision-making. Environmental indices simplify the complex impacts of various environmental fact...
Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.
Journal of agricultural and food chemistry
Apr 16, 2025
Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental a...
AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma.
Journal of nanobiotechnology
Apr 16, 2025
BACKGROUND: Lymphoma is a malignant tumor of the immune system and its incidence is increasing year after year, causing a major threat to people's health. Conventional diagnosis of lymphoma basically depends on histological images consuming long-time...
Achieving precision assessment of functional clinical scores for upper extremity using IMU-Based wearable devices and deep learning methods.
Journal of neuroengineering and rehabilitation
Apr 16, 2025
Stroke is a serious cerebrovascular disease, and rehabilitation following the acute phase is particularly crucial. Not all rehabilitation outcomes are favorable, highlighting the necessity for personalized rehabilitation. Precision assessment is esse...
Tuberculosis detection using few shot learning.
Scientific reports
Apr 16, 2025
Tuberculosis (TB), a contagious disease, significantly affects lungs functioning. Amongst multiple detection methodologies, Chest X-ray analysis is considered the most effective methodology. Traditional Deep Learning methodologies have shown good res...
An interpretable framework for gastric cancer classification using multi-channel attention mechanisms and transfer learning approach on histopathology images.
Scientific reports
Apr 16, 2025
The importance of gastric cancer (GC) and the role of deep learning techniques in categorizing GC histopathology images have recently increased. Identifying the drawbacks of traditional deep learning models, including lack of interpretability, inabil...
Attention LinkNet-152: a novel encoder-decoder based deep learning network for automated spine segmentation.
Scientific reports
Apr 16, 2025
Segmenting the spine from CT images is crucial for diagnosing and treating spine-related conditions but remains challenging due to the spine's complex anatomy and imaging artifacts. This study introduces a novel encoder-decoder-based deep learning ap...
Prediction of barberry witches' broom rust disease using artificial intelligence models: a case study in South Khorasan, Iran.
Scientific reports
Apr 16, 2025
The South Khorasan Province in Iran is the main producer of seedless barberry, accounting for 98% of the country's production. This has led to significant economic growth in the region. However, the cultivation of barberry is threatened by the rust f...
Deep learning-based automatic segmentation of cerebral infarcts on diffusion MRI.
Scientific reports
Apr 16, 2025
We explored effects of (1) training with various sample sizes of multi-site vs. single-site training data, (2) cross-site domain adaptation, and (3) data sources and features on the performance of algorithms segmenting cerebral infarcts on Magnetic R...
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