AIMC Topic: Unsupervised Machine Learning

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An unsupervised learning approach for clustering joint trajectories of Alzheimer's disease biomarkers: An application to ADNI Data.

Alzheimer's & dementia : the journal of the Alzheimer's Association Jan 27, 2025
INTRODUCTION: Current models of Alzheimer's disease (AD) progression assume a common pattern and pathology, oversimplifying the heterogeneity of clinical AD.
Humans Amyloid beta-Peptides Biomarkers Female Alzheimer Disease Cluster Analysis Male Brain Aged Neuroimaging Unsupervised Machine Learning Disease Progression
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

Scientific reports Jan 25, 2025
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and a...
Cluster Analysis Unsupervised Machine Learning Colonic Polyps Supervised Machine Learning Colonoscopy Support Vector Machine Algorithms Colorectal Neoplasms Humans Neural Networks, Computer
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Detecting noncredible symptomology in ADHD evaluations using machine learning.

Journal of clinical and experimental neuropsychology Jan 25, 2025
INTRODUCTION: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becoming increasingly complicated by the number of adults who fabricate or exaggerate symptoms. Novel methods are needed to improve the assessment process re...
Adult Attention Deficit Disorder with Hyperactivity Female Surveys and Questionnaires Male Malingering Young Adult Unsupervised Machine Learning Adolescent Middle Aged Self Report Humans Machine Learning
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Generative adversarial local density-based unsupervised anomaly detection.

PloS one Jan 24, 2025
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly...
Neural Networks, Computer Algorithms Computer Security Humans Unsupervised Machine Learning
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SAC-BL: A hypothesis testing framework for unsupervised visual anomaly detection and location.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Reconstruction-based methods achieve promising performance for visual anomaly detection (AD), relying on the underlying assumption that the anomalies cannot be accurately reconstructed. However, this assumption does not always hold, especially when s...
Algorithms Unsupervised Machine Learning Humans Neural Networks, Computer
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EHM: Exploring dynamic alignment and hierarchical clustering in unsupervised domain adaptation via high-order moment-guided contrastive learning.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Unsupervised domain adaptation (UDA) aims to annotate unlabeled target domain samples using transferable knowledge learned from the labeled source domain. Optimal transport (OT) is a widely adopted probability metric in transfer learning for quantify...
Cluster Analysis Unsupervised Machine Learning Neural Networks, Computer Humans Algorithms
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Real-Time Unsupervised Learning and Image Recognition via Memristive Neural Integrated Chip Based on Negative Differential Resistance of Electrochemical Metallization Cell Neuron Device.

Small (Weinheim an der Bergstrasse, Germany) Jan 21, 2025
Spiking neurons are essential for building energy-efficient biomimetic spatiotemporal systems because they communicate with other neurons using sparse and binary signals. However, the achievable high density of artificial neurons having a capacitor f...
Neural Networks, Computer Unsupervised Machine Learning Humans Neurons
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Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR.

Medical image analysis Jan 18, 2025
The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultrasound (ABUS) for lesion detection. Traditional methods based on single scans have fallen short compared to comprehensive evaluations by experienced sono...
Female Breast Neoplasms Imaging, Three-Dimensional Humans Algorithms Image Interpretation, Computer-Assisted Unsupervised Machine Learning Ultrasonography, Mammary
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Reducing bias in source-free unsupervised domain adaptation for regression.

Neural networks : the official journal of the International Neural Network Society Jan 17, 2025
Due to data privacy and storage concerns, Source-Free Unsupervised Domain Adaptation (SFUDA) focuses on improving an unlabelled target domain by leveraging a pre-trained source model without access to source data. While existing studies attempt to tr...
Unsupervised Machine Learning Bias Neural Networks, Computer Regression Analysis Humans
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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...
Humans Support Vector Machine Cluster Analysis Unsupervised Machine Learning Algorithms Supervised Machine Learning Risk Assessment
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