AIMC Topic: Principal Component Analysis

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A machine learning approach for age prediction based on trigeminal landmarks.

Journal of forensic and legal medicine
OBJECTIVE: The aim of this study was to estimate the chronological age (CA) of a growing individual using a new machine learning approach on Cone Beam Computed Tomography (CBCT).

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.

Methods (San Diego, Calif.)
Host defense or antimicrobial peptides (AMPs) are promising candidates for protecting host against microbial pathogens for example bacteria, virus, fungi, yeast. Defensins are the type of AMPs that act as potential therapeutic drug agent and perform ...

Machine Learning-Assisted Eu(III)-Functionalized HOF-on-HOF Composite-Based Sensor Platform for Precise and Visual Identification of Multiple Pesticides.

Analytical chemistry
Precise and rapid identification of pesticides is crucial to ensure a green environment, food safety, and human health. However, complex sample environments often hinder precise identification, especially for simultaneous differentiation of multiple ...

Enhancing early identification of high-fertile cattle females using infrared blood serum spectra and machine learning.

Scientific reports
Artificial insemination (AI) success in bovine reproduction is vital for the cattle industry's economic sustainability and for advancing the understanding of reproductive physiology. Identify high-fertile animals' fertility is a complex task due to m...

Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.

Scientific reports
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time...

Advancing breast ultrasound diagnostics through hybrid deep learning models.

Computers in biology and medicine
Today, doctors rely heavily on medical imaging to identify abnormalities. Proper classification of these abnormalities enables them to take informed actions, leading to early diagnosis and treatment. This paper introduces the "EfficientKNN" model, a ...

Euclidean-Distance-Preserved Feature Reduction for efficient person re-identification.

Neural networks : the official journal of the International Neural Network Society
Person Re-identification (Re-ID) aims to match person images across non-overlapping cameras. The existing approaches formulate this task as fine-grained representation learning with deep neural networks, which involves extracting image features using...

Machine Learning Using Template-Based-Predicted Structure of Haemagglutinin Predicts Pathogenicity of Avian Influenza.

Journal of microbiology and biotechnology
Deep learning presents a promising approach to complex biological classifications, contingent upon the availability of well-curated datasets. This study addresses the challenge of analyzing three-dimensional protein structures by introducing a novel ...

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

Biosensors
The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk ...

QCL Infrared Spectroscopy Combined with Machine Learning as a Useful Tool for Classifying Acetaminophen Tablets by Brand.

Molecules (Basel, Switzerland)
The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and class...