AIMC Topic: Principal Component Analysis

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Smartphone-Based SPAD Value Estimation for Jujube Leaves Using Machine Learning: A Study on RGB Feature Extraction and Hybrid Modeling.

Sensors (Basel, Switzerland) Apr 17, 2025
Chlorophyll content in date leaves is critical for fruit quality and yield. Traditional detection methods are usually complex and expensive. This study proposes a rapid detection method for chlorophyll content using smartphone images and machine lear...
Neural Networks, Computer Machine Learning Deep Learning Image Processing, Computer-Assisted Chlorophyll Principal Component Analysis Ziziphus Smartphone Color Plant Leaves
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Machine learning approaches for assessing medication transfer to human breast milk.

Journal of pharmacokinetics and pharmacodynamics Apr 16, 2025
The human milk/plasma (M/P) drug concentration ratio is crucial in pharmacology, especially for breastfeeding mothers undergoing treatment. It determines the extent to which drugs ingested by the mother pass into breast milk, potentially affecting th...
Support Vector Machine Principal Component Analysis Bayes Theorem Algorithms Humans Pharmaceutical Preparations Female Neural Networks, Computer Breast Feeding Milk, Human Machine Learning
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Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression.

ACS nano Apr 15, 2025
Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpre...
Humans Discriminant Analysis Machine Learning Amyloid beta-Peptides Alzheimer Disease Logistic Models COVID-19 Spectrum Analysis Support Vector Machine Algorithms Principal Component Analysis SARS-CoV-2
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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides.

Scientific reports Apr 14, 2025
Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) ...
Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Principal Component Analysis Algorithms Female Uterine Cervical Neoplasms Neural Networks, Computer Machine Learning Humans
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Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.

Scientific reports Apr 13, 2025
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...
Child Principal Component Analysis Cephalometry Cross-Sectional Studies Male Adolescent Germany Malocclusion, Angle Class III Malocclusion, Angle Class I Humans Machine Learning Young Adult Adult Prospective Studies Female
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Voice biomarkers as prognostic indicators for Parkinson's disease using machine learning techniques.

Scientific reports Apr 9, 2025
Many people suffer from Parkinson's disease globally, a complicated neurological condition caused by the deficiency of dopamine, an organic chemical responsible for regulating movement in individuals. Patients with Parkinson face muscle stiffness or ...
Humans Machine Learning Biomarkers Prognosis Principal Component Analysis Middle Aged Voice Support Vector Machine Parkinson Disease Female Aged Male
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Artificial neural networks applied to somatosensory evoked potentials for migraine classification.

The journal of headache and pain Apr 4, 2025
BACKGROUND: Finding a biomarker to diagnose migraine remains a significant challenge in the headache field. Migraine patients exhibit dynamic and recurrent alterations in the brainstem-thalamo-cortical loop, including reduced thalamocortical activity...
Migraine Disorders Principal Component Analysis Electroencephalography Sensitivity and Specificity Male Humans Middle Aged Young Adult Adult Evoked Potentials, Somatosensory Neural Networks, Computer Female
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An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.

Scientific reports Apr 4, 2025
Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous monitoring and early detection are necessary for effective management. The Metaverse Environment (ME) has gained attention in the digital healthcare e...
Algorithms Diabetes Mellitus Principal Component Analysis Stroke Humans Neural Networks, Computer
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N6-methyladenine identification using deep learning and discriminative feature integration.

BMC medical genomics Mar 29, 2025
N6-methyladenine (6 mA) is a pivotal DNA modification that plays a crucial role in epigenetic regulation, gene expression, and various biological processes. With advancements in sequencing technologies and computational biology, there is an increasin...
Adenine Humans Computational Biology Algorithms DNA Methylation Deep Learning Principal Component Analysis
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Cancer Cell Line Classification Using Raman Spectroscopy of Cancer-Derived Exosomes and Machine Learning.

Analytical chemistry Mar 27, 2025
Liquid biopsies are an emerging, noninvasive tool for cancer diagnostics, utilizing biological fluids for molecular profiling. Nevertheless, the current methods often lack the sensitivity and specificity necessary for early detection and real-time mo...
Principal Component Analysis Discriminant Analysis Exosomes Humans Machine Learning Spectrum Analysis, Raman Lipids Neoplasms Cell Line, Tumor
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