AIMC Topic: Deep Learning

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In-depth exploration of software defects and self-admitted technical debt through cutting-edge deep learning techniques.

PloS one Jun 11, 2025
Most previous research focuses on finding Self-Admitted Technical Debt (SATD) or detecting bugs alone, rather to addressing the concurrent identification of both issues. These study investigations solely identify and classify the SATD or faults, with...
Deep Learning Humans Software
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An ensemble-based 3D residual network for the classification of Alzheimer's disease.

PloS one Jun 11, 2025
Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a key precursor. Early MCI diagnosis is crucial for slowing AD progression, but distinguishing MCI from normal controls (NC) is challenging due to subtl...
Female Alzheimer Disease Humans Deep Learning Aged Male Neural Networks, Computer Cognitive Dysfunction
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Improving lung cancer diagnosis and survival prediction with deep learning and CT imaging.

PloS one Jun 11, 2025
Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial for improving patients' survival outcomes. In this paper, we propose to employ convolutional neural networks to model the non-linear relationship bet...
Neural Networks, Computer Tomography, X-Ray Computed Female Humans Male Lung Neoplasms Proportional Hazards Models Deep Learning
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High-Output Droplet Electricity Generator for Intelligent Self-Powered Biochemical Analysis.

Analytical chemistry Jun 10, 2025
The detection and analysis of chemical and biological substances are crucial in fields such as pharmaceuticals, disease diagnosis food safety and environmental monitoring. However, traditional analytical methods often involve complex procedures, expe...
Electricity Deep Learning Electrochemical Techniques
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SCATrans: semantic cross-attention transformer for drug-drug interaction predication through multimodal biomedical data.

BMC bioinformatics Jun 10, 2025
Predicting potential drug-drug interactions (DDIs) from biomedical data plays a critical role in drug therapy, drug development, drug regulation, and public health. However, it remains challenging due to the large number of possible drug combinations...
Computational Biology Drug Interactions Humans Semantics Algorithms Deep Learning
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Oil Palm Fruits Dataset in Plantations for Harvest Estimation Using Digital Census and Smartphone.

Scientific data Jun 10, 2025
This article presents a dataset of oil palm Fresh Fruit Bunches (FFBs) images from commercial plantations in Central Kalimantan, Indonesia, focusing on five maturity stages: Unripe, Underripe, Ripe, Flower, and Abnormal. The data collection involved ...
Deep Learning Smartphone Indonesia Fruit Agriculture Video Recording Arecaceae
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A plaque recognition algorithm for coronary OCT images by Dense Atrous Convolution and attention mechanism.

PloS one Jun 10, 2025
Currently, plaque segmentation in Optical Coherence Tomography (OCT) images of coronary arteries is primarily carried out manually by physicians, and the accuracy of existing automatic segmentation techniques needs further improvement. To furnish eff...
Image Processing, Computer-Assisted Tomography, Optical Coherence Coronary Vessels Plaque, Atherosclerotic Coronary Artery Disease Humans Algorithms Deep Learning
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Robust Bayesian brain extraction by integrating structural subspace-based spatial prior into deep neural networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 9, 2025
Accurate and robust brain extraction, or skull stripping, is essential for studying brain development, aging, and neurological disorders. However, brain images exhibit substantial data heterogeneity due to differences in contrast and geometric charac...
Bayes Theorem Brain Adult Image Processing, Computer-Assisted Magnetic Resonance Imaging Deep Learning Humans Neural Networks, Computer
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Deep learning-based post-hoc noise reduction improves quarter-radiation-dose coronary CT angiography.

European journal of radiology Jun 9, 2025
PURPOSE: To evaluate the impact of deep learning-based post-hoc noise reduction (DLNR) on image quality, coronary artery disease reporting and data system (CAD-RADS) assessment, and diagnostic performance in quarter-dose versus full-dose coronary CT ...
Retrospective Studies Female Aged Humans Deep Learning Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Male Middle Aged Signal-To-Noise Ratio Computed Tomography Angiography Coronary Artery Disease Radiation Dosage
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Differentiating Bacterial and Non-Bacterial Pneumonia on Chest CT Using Multi-Plane Features and Clinical Biomarkers.

Academic radiology Jun 9, 2025
RATIONALE AND OBJECTIVES: Timely and accurate classification of bacterial pneumonia (BP) is essential for guiding antibiotic therapy. However, distinguishing BP from non-bacterial pneumonia (NBP) using computed tomography (CT) is challenging due to o...
Male Middle Aged Deep Learning Adult Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Pneumonia, Bacterial Diagnosis, Differential Pneumonia Biomarkers Retrospective Studies Female Aged Tomography, X-Ray Computed Humans
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