Machine learning automates material analysis and design using X-ray spectroscopy data

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy ...
IEEE

A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification

Abstract: High-quality labeled samples of polarimetric synthetic aperture radar (PolSAR) images are relatively scarce. Therefore, achieving optimal classification performance with limited labeled ...
IEEE

An Optimized Credit Card Fraud Detection Using Balancing Techniques: A Comparative Machine Learning Study Sampling & Testing Integrated

Abstract: Credit card fraud is a massive problem for financial institutions and consumers due to the intrinsic imbalance between legitimate and fraudulent transactions in data sets. The implementation ...
ahajournals.org

Claims‐Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke

We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and ...
National Hockey League

Winning (and learning): Stars still learning, growing amid successful start to season

One of the old adages in hockey is that a great time to learn is when you’re collecting points. The philosophy is that if you are playing below your pedigree, your team is clearly aware. And if you ...
C&EN

Alumina-Supported Catalyst Development for Propane Dehydrogenation via Interpretable Machine Learning and Experimental Validation

State Key Laboratory of Fine Chemicals, Liaoning Key Laboratory for Catalytic Conversion of Carbon Resources, School of Chemistry, School of Chemical Engineering, Dalian University of Technology, ...