AIMC Topic: Ensemble Learning

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Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

Computers in biology and medicine Jan 24, 2025
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmenta...
Humans Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Deep Learning Ensemble Learning Convolutional Neural Networks Neural Networks, Computer Image Processing, Computer-Assisted Machine Learning Brain Neoplasms
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study.

JMIR medical informatics Jan 20, 2025
BACKGROUND: The prompt and accurate identification of mild cognitive impairment (MCI) is crucial for preventing its progression into more severe neurodegenerative diseases. However, current diagnostic solutions, such as biomarkers and cognitive scree...
Wearable Electronic Devices Cognitive Dysfunction Ensemble Learning Aged, 80 and over Male Middle Aged Female Aged Humans Machine Learning
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Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.

Biomedical physics & engineering express Jan 17, 2025
This study aimed to develop and evaluate an efficient method to automatically segment T1- and T2-weighted brain magnetic resonance imaging (MRI) images. We specifically compared the segmentation performance of individual convolutional neural network ...
Radiotherapy Planning, Computer-Assisted Radiotherapy, Image-Guided Ensemble Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Organs at Risk Humans Neural Networks, Computer Algorithms Brain Brain Neoplasms Deep Learning
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Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.

IEEE transactions on neural networks and learning systems Jan 7, 2025
Introducing deep learning technologies into the medical image processing field requires accuracy guarantee, especially for high-resolution images relayed through endoscopes. Moreover, works relying on supervised learning are powerless in the case of ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Supervised Machine Learning Ensemble Learning Laryngoscopy Algorithms Colonoscopy Deep Learning
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DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 4, 2025
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to q...
Adult Deep Learning Brain Diseases Ensemble Learning Humans Neural Networks, Computer Brain Uncertainty Diffusion Magnetic Resonance Imaging
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Improving groundwater quality predictions in semi-arid regions using ensemble learning models.

Environmental science and pollution research international Jan 4, 2025
Groundwater resources constitute one of the primary sources of freshwater in semi-arid and arid climates. Monitoring the groundwater quality is an essential component of environmental management. In this study, a comprehensive comparison was conducte...
Environmental Monitoring Iran Water Quality Ensemble Learning Machine Learning Desert Climate Neural Networks, Computer Groundwater
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An ensemble learning method combined with multiple feature representation strategies to predict lncRNA subcellular localizations.

Computational biology and chemistry Jan 1, 2025
Long non-coding RNAs (lncRNAs) are strongly associated with cellular physiological mechanisms and implicated in the numerous diseases. By exploring the subcellular localizations of lncRNAs, we can not only gain crucial insights into the molecular mec...
Humans Machine Learning Ensemble Learning Algorithms Computational Biology RNA, Long Noncoding
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Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.

European journal of radiology Dec 24, 2024
OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is challenging due to their similar imaging features on conventional brain MRI. This study aimed to enhance diagnostic accuracy through a machine learning ...
Image Interpretation, Computer-Assisted Adult Ensemble Learning Sensitivity and Specificity Magnetic Resonance Imaging Radiomics Diagnosis, Differential Brain Neoplasms Female Humans Glioblastoma Male Machine Learning Middle Aged Reproducibility of Results Retrospective Studies Aged
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Deepstack-ACE: A deep stacking-based ensemble learning framework for the accelerated discovery of ACE inhibitory peptides.

Methods (San Diego, Calif.) Dec 19, 2024
Identifying angiotensin-I-converting enzyme (ACE) inhibitory peptides accurately is crucial for understanding the primary factor that regulates the renin-angiotensin system and for providing guidance in developing new potential drugs. Given the inher...
Humans Deep Learning Peptidyl-Dipeptidase A Neural Networks, Computer Angiotensin-Converting Enzyme Inhibitors Ensemble Learning Peptides Drug Discovery
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Ensemble learning-assisted quantitative identifying influencing factors of cadmium and arsenic concentration in rice grain based multiplexed data.

Journal of hazardous materials Dec 14, 2024
Rapid and accurate prediction of rice Cd (rCd) and rice As (rAs) bioaccumulation are important for assessing the safe utilization of rice. Currently, there is lack of comprehensive and systematic exploration of the factors of rCd and rAs. Herein, ens...
Arsenic Edible Grain Oryza Cadmium Ensemble Learning Environmental Monitoring Food Contamination Machine Learning Soil Pollutants Soil China
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