Proceedings of the National Academy of Sciences (PNAS)

Identifying variation in dinosaur footprints and classifying problematic specimens via unbiased unsupervised machine learning

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Frontiers

Compare the prognosis of pancreatic cancer patients with different treatment modalities and use machine learning methods to build predictive models

Background: Pancreatic cancer (PC) is highly refractory to most treatments. Multimodal treatment, combining several types of therapies, is likely to benefit PC patients. However, it remains unclear ...
IEEE

Leveraging Machine Learning Algorithms for Robust Credit Card Fraud Detection: A Performance Comparison

Abstract: The implementation of systems designed to detect cyber crimes has become essential for banks and other financial institutions. A variety of approaches have been proposed to combat the ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Frontiers

Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...
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 ...
IEEE

Multiple Machine Learning Algorithms Comparison for Modulation Type Classification for Efficient Cognitive Radio

Abstract: In this paper the potential of improving channel utilization by signal modulation type classification based on machine learning algorithms has been studied. The classification has been ...