marktechpost

Kernel Principal Component Analysis (PCA): Explained with an Example

Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...
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

Comparative analysis of machine learning techniques on the BraTS dataset for brain tumor classification

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...
ascopubs.org

Association of deep learning CT response assessment and interpretable components with overall survival in advanced NSCLC: Validation in a trial of sasanlimab and a real-world ...

Use of a large language model (LLM) for pan-cancer automated detection of anti-cancer therapy toxicities and translational toxicity research. Computational pathology to predict docetaxel benefit in ...
The Daily Northwestern

Q&A: Outgoing ETHS principal discusses social emotional learning, strengthening school community

Taya Kinzie, the outgoing principal of Evanston Township High School and assistant superintendent of ETHS District 202, said she has always bled blue and orange. Her children, sisters, mother, ...
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 ...
Forbes

How AI, Data Science, And Machine Learning Are Shaping The Future

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...
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 ...
IEEE

Advancing Smart Grid Stability Through Machine Learning and Principal Component Analysis

Abstract: Innovative solutions are required to maintain the stability, efficiency, and dependability of modern smart grid systems due to their increasing complexity and demand. This paper explores the ...
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, ...