Researchers have developed machine learning models that predict the likelihood of critical events and mortality in COVID-19 patients within clinically relevant time windows. «From the initial outburst of COVID-19 in New York City, we saw that COVID-19 presentation and disease course are heterogeneous and we have built machine learning models using patient data to predict…

Researchers reveal a new method for analyzing hierarchies in complex networks and illustrate it by applications to economics, language and gene expression. A prime example of this is a food web, in which the nodes represent species and there is a directed edge from each species to those which eat it. In a directed network,…

When it comes to understanding and predicting trends in energy use, the internet is a tough nut to crack. So say energy researchers in two recent articles that discuss the pitfalls that plague estimates of the internet’s energy and carbon impacts. The paper describes how these errors can lead well-intentioned studies to predict massive energy…

Researchers in the life sciences who use machine learning for their studies should adopt standards that allow other researchers to reproduce their results, according to a new article. The authors explain that the standards are key to advancing scientific breakthroughs, making advances in knowledge, and ensuring research findings are reproducible from one group of scientists…

Researchers have modeled COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning. Researchers from Florida Atlantic University’s College of Engineering and Computer Science are the first to model COVID-19 completion versus cessation in clinical trials using machine learning algorithms and ensemble learning. The study, published in PLOS ONE, provides the…

Researchers have developed a machine learning-based model to predict the characteristics of bonded systems. Using the density of states of the individual component reactants, they have achieved accurate predictions of the binding energy, bond length, number of covalent electrons, and Fermi energy. The broadly applicable model is expected to make a significant contribution to the…

A new machine-learning model that generates realistic seismic waveforms will reduce manual labor and improve earthquake detection, according to a new study. «To verify the e?cacy of our generative model, we applied it to seismic ?eld data collected in Oklahoma,» said Youzuo Lin, a computational scientist in Los Alamos National Laboratory’s Geophysics group and principal…

A new algorithm uses online learning to analyze large single-cell data sets using the amount of memory found on a standard laptop computer. A relatively recent technique called single-cell sequencing is enabling researchers to recognize and categorize cell types by characteristics such as which genes they express. But this type of research generates enormous amounts…

Artificial intelligence (AI) models that evaluate medical images have potential to speed up and improve accuracy of cancer diagnoses, but they may also be vulnerable to cyberattacks. Researchers simulated an attack that falsified mammogram images, fooling both an AI breast cancer diagnosis model and human breast imaging radiologist experts. The study, published today in Nature…

Enzymes are biological catalysts that facilitate biochemical transformations. An international team of bioinformatics researchers has developed a new process for predicting Michaelis constants, which determine reaction kinetics. To describe metabolic processes facilitated by enzymes, scientists refer to what is known as the Michaelis-Menten equation. The equation describes the rate of an enzymatic reaction depending on…