Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...
A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...
This guest essay reflects the views of Nirali Somia, a graduate student at Cold Spring Harbor Laboratory. It is part of a series of essays from current researchers at the Cold Spring Harbor Laboratory ...
Discover how explainable AI enhances Parkinson’s disease prediction with improved accuracy and clinical interpretability.
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
A new review in Science China Life Sciences examines how machine learning and host-microbiome multi-omics can be combined to better understand health and disease. The article outlines the road from ...
The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
From batteries to catalysts, electrochemistry is getting a major boost from machine learning and advanced computational models. Researchers are now predicting redox potentials, ion migration, and ...
Researchers have published research detailing their development of an AI framework to detect defects in additively ...
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