AIMC Topic: Principal Component Analysis

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Analyzing the impact of clay minerals on the reservoir quality of the Lower Goru Formation using Unsupervised Machine Learning.

PloS one Jan 1, 2025
The reservoir quality of the Lower Goru Formation is highly variable due to its heterogeneous nature influenced by sea level fluctuations during the Early Cretaceous period. This study applies an unsupervised machine learning workflow, integrating Pr...
Unsupervised Machine Learning Principal Component Analysis Aluminum Silicates Clay Geologic Sediments Minerals Pakistan
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Unsupervised Dimensionality Reduction Techniques for the Assessment of ASD Biomarkers.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2025
Autism Spectrum Disorder (ASD) encompasses a range of developmental disabilities marked by differences in social functioning, cognition, and behavior. Both genetic and environmental factors are known to contribute to ASD, yet the exact etiological fa...
Humans Supervised Machine Learning Neuroimaging Male Child Unsupervised Machine Learning Principal Component Analysis Computational Biology Autism Spectrum Disorder Female Algorithms Biomarkers
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Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research.

Studies in health technology and informatics Nov 22, 2024
This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to c...
Machine Learning Neoplasms Humans Databases, Protein Principal Component Analysis Peptides Antineoplastic Agents
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Optimizing ICU Care: Machine Learning and PCA for Early Prediction of Renal Replacement Therapy Requirement.

Studies in health technology and informatics Aug 22, 2024
Forecasting the need for Renal Replacement Therapy (RRT) in intensive care units (ICUs) at an early stage can enhance patient outcomes and optimize resource allocation. The study aimed to develop a model for early prediction of Renal Replacement Ther...
Critical Care Machine Learning Renal Replacement Therapy Male Principal Component Analysis Intensive Care Units Humans
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[Automatic epilepsy detection with an attention-based multiscale residual network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2024
The deep learning-based automatic detection of epilepsy electroencephalogram (EEG), which can avoid the artificial influence, has attracted much attention, and its effectiveness mainly depends on the deep neural network model. In this paper, an atten...
Signal Processing, Computer-Assisted Electroencephalography Epilepsy Humans Neural Networks, Computer Deep Learning Algorithms Principal Component Analysis
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A Novel Detection of Cerebrovascular Disease using Multimodal Medical Image Fusion.

Recent advances in inflammation & allergy drug discovery Jan 1, 2024
BACKGROUND: Diseases are medical situations that are allied with specific signs and symptoms. A disease may be instigated by internal dysfunction or external factors like pathogens. Cerebrovascular disease can progress from diverse causes, comprising...
Humans Machine Learning Support Vector Machine Magnetic Resonance Imaging Tomography, X-Ray Computed Cerebrovascular Disorders Fourier Analysis Multimodal Imaging Principal Component Analysis
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Feature Learning Networks for Floor Sensor-based Gait Recognition.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Deep learning (DL) has become a powerful tool in many image classification applications but often requires large training sets to achieve high accuracy. For applications where the available data are limited, this can become a severely limiting factor...
Gait Wavelet Analysis Neural Networks, Computer Principal Component Analysis Humans
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Effects of dimension reduction of hyperspectral images in skin gross pathology.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) Feb 1, 2023
BACKGROUND: Hyperspectral imaging (HSI) is an emerging modality for the gross pathology of the skin. Spectral signatures of HSI could discriminate malignant from benign tissue. Because of inherent redundancies in HSI and in order to facilitate the us...
Principal Component Analysis Random Forest Humans Support Vector Machine
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Comparison of preprocessing techniques to reduce nontissue-related variations in hyperspectral reflectance imaging.

Journal of biomedical optics Oct 1, 2022
SIGNIFICANCE: Hyperspectral reflectance imaging can be used in medicine to identify tissue types, such as tumor tissue. Tissue classification algorithms are developed based on, e.g., machine learning or principle component analysis. For the developme...
Principal Component Analysis Hyperspectral Imaging Spectroscopy, Near-Infrared Algorithms Support Vector Machine
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[Rapid identification of geographic origins of Zingiberis Rhizoma by NIRS combined with chemometrics and machine learning algorithms].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica Sep 1, 2022
In this study, 280 batches of Zingiberis Rhizoma samples from nine producing areas were analyzed to obtain infrared spectral information based on near-infrared spectroscopy(NIRS). Pluralistic chemometrics such as principal component analysis(PCA), pa...
Principal Component Analysis Plant Extracts Least-Squares Analysis Algorithms Support Vector Machine Chemometrics China Zingiber officinale
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