AZoLifeSciences on MSN

Machine learning models identify early metabolic shifts

Acute systemic inflammation has long been suspected to trigger harmful processes within the brain, contributing to ...
Analytics Insight

Data Science: Building Machine Learning Models, Harvard University

Harvard University presents its eight-week online course through edX, which imparts to students essential knowledge of ...
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
Risk.net

Volume 17, Number 4 (December 2025)

This issue of The Journal of Energy Markets goes to press at a time of unprecedented structural transformation in the global energy landscape, shaped by accelerating climate and decarbonization ...
SciELO

Precision crack analysis in concrete structures using CNN, SVM, and KNN: a machine learning approach

Cracks in structures are discontinuities that occur due to stress, material degradation, or design flaws, compromising structural integrity. Detecting and analyzing cracks is crucial for assessing ...
Frontiers

Integrated machine learning and single-cell RNA sequencing reveal COL4A2 and CXCL6 as oxidative stress-associated biomarkers in periodontitis

Background: Periodontitis, recognized as the second most prevalent oral disease globally, is strongly linked to systemic disorders like diabetes and cardiovascular diseases, highlighting the critical ...
C&EN

Automated Machine-Learning-Driven Analysis of Microplastics by TGA-FTIR for Enhanced Identification and Quantification

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Microplastics persist as ubiquitous environmental contaminants, and efficient methods ...
C&EN

Open-Source Visual Programming Software for Introducing Principal Component Analysis to the Analytical Curriculum

Principal component analysis (PCA) is one of the most common exploratory data analysis techniques with applications in outlier detection, dimensionality reduction, graphical clustering, and ...
Science Daily

'Democratizing chemical analysis':Chemists use machine learning and robotics to identify chemical compositions from images

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...
Frontiers

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia

Jiangxi Province Key Laboratory of Immunology and Inflammation, Jiangxi Provincial Clinical Research Center for Laboratory Medicine, Department of Clinical Laboratory, The Second Affiliated Hospital, ...
IEEE

A Method of Kernel Principal Component Analysis and Machine Learning Algorithms for Fault Diagnosis of Power Transformers

Abstract: As one of the most important equipment in the power system, it is of great significance to conduct fault diagnosis research on transformers. Aiming at the problem of difficult selection of ...