Recent advances and applications of machine learning in solid-state materials science
One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …
is machine learning. This collection of statistical methods has already proved to be capable …
A survey on text classification algorithms: From text to predictions
In recent years, the exponential growth of digital documents has been met by rapid progress
in text classification techniques. Newly proposed machine learning algorithms leverage the …
in text classification techniques. Newly proposed machine learning algorithms leverage the …
Computational redesign of a PETase for plastic biodegradation under ambient condition by the GRAPE strategy
Nature has provided a fantastic array of enzymes that are responsible for essential
biochemical functions but not usually suitable for technological applications. Not content …
biochemical functions but not usually suitable for technological applications. Not content …
Review of bridge structural health monitoring aided by big data and artificial intelligence: From condition assessment to damage detection
Structural health monitoring (SHM) techniques have been widely used in long-span bridges.
However, due to limitations of computational ability and data analysis methods, the …
However, due to limitations of computational ability and data analysis methods, the …
Hyperparameter optimization: Comparing genetic algorithm against grid search and bayesian optimization
H Alibrahim, SA Ludwig - 2021 IEEE Congress on Evolutionary …, 2021 - ieeexplore.ieee.org
The performance of machine learning algorithms are affected by several factors, some of
these factors are related to data quantity, quality, or its features. Another element is the …
these factors are related to data quantity, quality, or its features. Another element is the …
Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt
This study investigates whether coupling crop modeling and machine learning (ML)
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …
improves corn yield predictions in the US Corn Belt. The main objectives are to explore …
AI-driven tools for coronavirus outbreak: need of active learning and cross-population train/test models on multitudinal/multimodal data
KC Santosh - Journal of medical systems, 2020 - Springer
Abstract The novel coronavirus (COVID-19) outbreak, which was identified in late 2019,
requires special attention because of its future epidemics and possible global threats …
requires special attention because of its future epidemics and possible global threats …
A systematic literature review on phishing email detection using natural language processing techniques
Every year, phishing results in losses of billions of dollars and is a major threat to the Internet
economy. Phishing attacks are now most often carried out by email. To better comprehend …
economy. Phishing attacks are now most often carried out by email. To better comprehend …
A review of epileptic seizure detection using machine learning classifiers
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …
signals produced by brain neurons. Neurons are connected to each other in a complex way …
From hype to reality: data science enabling personalized medicine
Abstract Background Personalized, precision, P4, or stratified medicine is understood as a
medical approach in which patients are stratified based on their disease subtype, risk …
medical approach in which patients are stratified based on their disease subtype, risk …