AIMC Topic: Cluster Analysis
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Machine Learning-based Cluster Analysis Identifies Three Unique Phenotypes of Patients With Adult Spinal Deformity With Distinct Clinical Profiles and Long-term Recovery Trajectory: A Development Study.
Spine
Jan 21, 2025
STUDY DESIGN: A retrospective review of a prospective adult spinal deformity data.
Deep Clustering for Epileptic Seizure Detection.
IEEE transactions on bio-medical engineering
Jan 21, 2025
UNLABELLED: Epilepsy is a neurological disorder characterized by recurrent epileptic seizures, which are often unpredictable and increase mortality and morbidity risks.
An efficient framework based on local multi-representatives and noise-robust synthetic example generation for self-labeled semi-supervised classification.
Neural networks : the official journal of the International Neural Network Society
Jan 16, 2025
While self-labeled methods can exploit unlabeled and labeled instances to train classifiers, they are also restricted by the labeled instance number and distribution. SEG-SSC, k-means-SSC, LC-SSC, and LCSEG-SSC are sophisticated solutions for overcom...
Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.
Viruses
Jan 15, 2025
Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and res...
Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning.
Scientific reports
Jan 15, 2025
To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease is required. We performed invariant information clustering (IIC)-based clustering on glomerular images obtained from nephrectomized kidneys of patients...
Prediction and unsupervised clustering of fertility intention among migrant workers based on machine learning: a cross-sectional survey from Henan, China.
BMC public health
Jan 14, 2025
BACKGROUND: Although China has implemented multiple policies to encourage childbirth, the results have been underwhelming. Migrant workers account for a considerable proportion of China's population, most of whom are of childbearing age. However, few...
A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment.
PloS one
Jan 10, 2025
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performanc...
The impact of preschool children's physical fitness evaluation under self organizing maps neural network.
Scientific reports
Jan 9, 2025
To improve the scientific accuracy and precision of children's physical fitness evaluations, this study proposes a model that combines self-organizing maps (SOM) neural networks with cluster analysis. Existing evaluation methods often rely on traditi...
Clustering-based binary Grey Wolf Optimisation model with 6LDCNNet for prediction of heart disease using patient data.
Scientific reports
Jan 8, 2025
In recent years, the healthcare data system has expanded rapidly, allowing for the identification of important health trends and facilitating targeted preventative care. Heart disease remains a leading cause of death in developed countries, often lea...
Dynamic Subcluster-Aware Network for Few-Shot Skin Disease Classification.
IEEE transactions on neural networks and learning systems
Jan 7, 2025
This article addresses the problem of few-shot skin disease classification by introducing a novel approach called the subcluster-aware network (SCAN) that enhances accuracy in diagnosing rare skin diseases. The key insight motivating the design of SC...
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