AIMC Topic: Principal Component Analysis
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Exploring the potential of machine learning in gastric cancer: prognostic biomarkers, subtyping, and stratification.
BMC cancer
Apr 30, 2025
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biomarkers in GC prognosis. Machine-learning (ML)-based methods can be applied to identify the most impo...
B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.
Clinical rheumatology
Apr 29, 2025
OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in patients with primary Sjögren's syndrome (pSS) and to investigate their associations with lymphoma risk, clinical phenotypes, and disease activity.
EEG-based epilepsy detection using CNN-SVM and DNN-SVM with feature dimensionality reduction by PCA.
Scientific reports
Apr 24, 2025
This study focuses on epilepsy detection using hybrid CNN-SVM and DNN-SVM models, combined with feature dimensionality reduction through PCA. The goal is to evaluate the effectiveness and performance of these models in accurately identifying epilepti...
LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data.
Proceedings of the National Academy of Sciences of the United States of America
Apr 23, 2025
Disease and behavior subtype identification is of significant interest in biomedical research. However, in many settings, subtype discovery is limited by a lack of robust statistical clustering methods appropriate for binary data. Here, we introduce ...
Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.
Scientific reports
Apr 21, 2025
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...
Rapid and chemical-free technique based on hyperspectral imaging combined with artificial intelligence for monitoring quality and shelf life of dried shrimp.
Food research international (Ottawa, Ont.)
Apr 18, 2025
A rapid and chemical-free method based on hyperspectral imaging (HSI) integrated with artificial intelligence (AI) for monitoring dried shrimp quality was developed. Dried shrimp was packaged in a polypropylene bag and chronologically monitored for c...
A sustainable system for predicting appliance energy consumption based on machine learning.
Journal of environmental management
Apr 18, 2025
Nowadays, energy conservation is a top priority for sustainable societies, which focus on environmental and economic sustainability to address fossil fuel scarcity, climate change, and increasing environmental pollution. Therefore, planning for energ...
Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN).
Nutrients
Apr 18, 2025
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance A...
Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.
Scientific reports
Apr 18, 2025
This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differential anti-vascular endothelial growth factor (VEGF) treatment outcomes using an unsupervised machine learning (ML) approach based on radiomic feature...
Visual Acuity
Principal Component Analysis
Tomography, Optical Coherence
Macular Edema
Treatment Outcome
Cluster Analysis
Unsupervised Machine Learning
Vascular Endothelial Growth Factor A
Retrospective Studies
Female
Aged
Radiomics
Male
Middle Aged
Angiogenesis Inhibitors
Humans
Diabetic Retinopathy
BL-FlowSOM: Consistent and Highly Accelerated FlowSOM Based on Parallelized Batch Learning.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Apr 17, 2025
The recent increase in the dimensionality of cytometry data has led to the development of various computational analysis methods. FlowSOM is one of the best-performing clustering methods but has room for improvement in terms of the consistency and sp...
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