Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Non-canonical amino acids can expand the scope of proteins available for therapeutics and machine learning platforms can ...

In the advancing modern world, AI is acting to transform the landscape of technology by reshaping industries and changing the methods of interaction with the digital world. It has solved the most ...

As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

A recent study has revealed that specific patterns of gene activity serve as a hidden map that guides the complex wiring of the entire brain. By using machine learning to analyze mouse brain data, ...

From specialized motors to the use of machine-learning algorithms, Turkey’s billion-dollar hair-transplant industry is the result of a constant process of innovation.

Abstract: Learning over time for machine learning (ML) models is emerging as a new field, often called continual learning or lifelong Machine learning (LML). Today, deep learning and neural networks ...

Abstract: Traffic control optimization is a challenging task for various traffic centers around the world and the majority of existing approaches focus only on developing adaptive methods for normal ...

Genome editing has advanced at a rapid pace with promising results for treating genetic conditions -- but there is always room for improvement. A new paper showcases the power of scalable protein ...

In a new study published in Nature titled, “Custom CRISPR-Cas9 PAM variants via scalable engineering and machine learning,” researchers from Massachusetts General Hospital (MGH) and Harvard Medical ...

For the last few years or so, the story in the artificial intelligence that was accepted without question was that all of the big names in the field needed more compute, more resources, more energy, ...