AIMC Topic: Cluster Analysis

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Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment.

Journal of translational medicine Jan 6, 2025
INTRODUCTION: Cardiac arrest (CA), characterized by its heterogeneity, poses challenges in patient management. This study aimed to identify clinical subphenotypes in CA patients to aid in patient classification, prognosis assessment, and treatment de...
Heart Arrest Middle Aged Treatment Outcome Cluster Analysis Humans Machine Learning Phenotype Aged Male Prognosis Female
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Multi-view clustering based on feature selection and semi-non-negative anchor graph factorization.

Neural networks : the official journal of the International Neural Network Society Jan 3, 2025
Multi-view clustering has garnered significant attention due to its capacity to utilize information from multiple perspectives. The concept of anchor graph-based techniques was introduced to manage large-scale data better. However, current methods re...
Humans Neural Networks, Computer Machine Learning Algorithms Cluster Analysis
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Fibrosis and inflammatory activity diagnosis of chronic hepatitis C based on extreme learning machine.

Scientific reports Jan 2, 2025
The traditional diagnosis of chronic hepatitis C usually relies on liver biopsy. Diagnosing chronic hepatitis C based on serum indices provides a non-invasive way to determine the stage of chronic hepatitis C without liver biopsy. In this paper, we p...
Humans Machine Learning Inflammation Cluster Analysis Biomarkers Hepatitis C, Chronic Liver Cirrhosis Female Male
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NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research Dec 31, 2024
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...
Proteomics Cluster Analysis Databases, Protein Tandem Mass Spectrometry Software Sequence Analysis, Protein Peptides Deep Learning
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Identification and Classification of Images in e-Cigarette-Related Content on TikTok: Unsupervised Machine Learning Image Clustering Approach.

Substance use & misuse Dec 30, 2024
BACKGROUND: Previous studies identified e-cigarette content on popular video and image-based social media platforms such as TikTok. While machine learning approaches have been increasingly used with text-based social media data, image-based analysis ...
Unsupervised Machine Learning Vaping Electronic Nicotine Delivery Systems Image Processing, Computer-Assisted Cluster Analysis Social Media Humans
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A new distal radius fracture classification depending on the specific fragments through machine learning clustering method.

BMC musculoskeletal disorders Dec 30, 2024
PURPOSES: The objective of this study was to investigate intra-articular distal radius fractures, aiming to provide a comprehensive analysis of fracture patterns and discuss the corresponding treatment strategies for each pattern.
Aged, 80 and over Young Adult Adult Male Middle Aged Treatment Outcome Bone Plates Hand Strength Retrospective Studies Radiography Radius Fractures Wrist Joint Female Follow-Up Studies Range of Motion, Articular Wrist Fractures Aged Fracture Fixation, Internal Humans Intra-Articular Fractures Cluster Analysis Machine Learning
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Leveraging feature extraction and risk-based clustering for advanced fault diagnosis in equipment.

PloS one Dec 30, 2024
In the contemporary manufacturing landscape, the advent of artificial intelligence and big data analytics has been a game-changer in enhancing product quality. Despite these advancements, their application in diagnosing failure probability and risk r...
Cluster Analysis Equipment Failure Humans Artificial Intelligence Algorithms
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Clustering and classification for dry bean feature imbalanced data.

Scientific reports Dec 28, 2024
The traditional machine learning methods such as decision tree (DT), random forest (RF), and support vector machine (SVM) have low classification performance. This paper proposes an algorithm for the dry bean dataset and obesity levels dataset that c...
Obesity Decision Trees Fabaceae Algorithms Support Vector Machine Cluster Analysis Humans Machine Learning
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Hypothesis generation for rare and undiagnosed diseases through clustering and classifying time-versioned biological ontologies.

PloS one Dec 26, 2024
Rare diseases affect 1-in-10 people in the United States and despite increased genetic testing, up to half never receive a diagnosis. Even when using advanced genome sequencing platforms to discover variants, if there is no connection between the var...
Phenotype Cluster Analysis Biological Ontologies Rare Diseases Humans Undiagnosed Diseases
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Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.

Journal of cardiovascular electrophysiology Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Middle Aged Risk Assessment Time Factors Risk Factors Aged Male Predictive Value of Tests Atrial Fibrillation Heart Rate Catheter Ablation Treatment Outcome Cluster Analysis Action Potentials Humans Machine Learning Decision Support Techniques Recurrence Phenotype Female Reproducibility of Results
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