AIMC Topic: Algorithms
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Ensemble machine learning-based pre-trained annotation approach for scRNA-seq data using gradient boosting with genetic optimizer.
BMC bioinformatics
Jul 1, 2025
Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression by allowing researchers to analyze the transcriptomes of individual cells. This technology provides unprecedented insights into cellular heterogeneity, cellular st...
Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis.
Scientific reports
Jul 1, 2025
Periodontitis, a chronic inflammatory condition of the periodontium, is associated with over 60 systemic diseases. Despite advancements, precision medicine approaches have had limited success, emphasizing the need for deeper insights into cellular su...
A hybrid XAI-driven deep learning framework for robust GI tract disease diagnosis.
Scientific reports
Jul 1, 2025
The stomach is one of the main digestive organs in the GIT, essential for digestion and nutrient absorption. However, various gastrointestinal diseases, including gastritis, ulcers, and cancer, affect health and quality of life severely. The precise ...
A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.
Scientific reports
Jul 1, 2025
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
An advanced fire detection system for assisting visually challenged people using recurrent neural network and sea-horse optimizer algorithm.
Scientific reports
Jul 1, 2025
The developing elderly population undergoes a high level of eyesight and mental impairment, which frequently results in a defeat of independence. That kind of person should do vital daily tasks like heating and cooking, with methods and devices inten...
CFM-UNet: coupling local and global feature extraction networks for medical image segmentation.
Scientific reports
Jul 1, 2025
In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conversely, Mamba, a novel network framework, effectively captures long-range feature dependencies and e...
Hybrid model integration with explainable AI for brain tumor diagnosis: a unified approach to MRI analysis and prediction.
Scientific reports
Jul 1, 2025
Effective treatment for brain tumors relies on accurate detection because this is a crucial health condition. Medical imaging plays a pivotal role in improving tumor detection and diagnosis in the early stage. This study presents two approaches to th...
Transformer attention fusion for fine grained medical image classification.
Scientific reports
Jul 1, 2025
Fine-grained visual classification is fundamental for medical image applications because it detects minor lesions. Diabetic retinopathy (DR) is a preventable cause of blindness, which requires exact and timely diagnosis to prevent vision damage. The ...
Super-resolution of 3D medical images by generative adversarial networks with long and short-term memory and attention.
Scientific reports
Jul 1, 2025
Since 3D medical imaging data is a string of sequential images, there is a strong correlation between consecutive images. Deep convolutional networks perform well in extracting spatial features, but are less capable for processing sequence data compa...
Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques.
Scientific reports
Jul 1, 2025
Breast cancer remains a major cause of mortality among women, where early and accurate detection is critical to improving survival rates. This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical...
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