Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Researchers developed a machine learning model that predicts high-yield antibody-producing cell lines early in manufacturing, ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

As instigators of immunity, monoclonal antibodies are marvels of modern medicine, lab-made proteins that can treat cancers, ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...