Abstract Machine learning (ML) holds promise for precision psychiatry, but its predictive
performance is unclear. We assessed whether ML provided added value over logistic …

We discover a robust self-supervised strategy tailored toward molecular representations for
generative masked language models through a series of tailored, in-depth ablations. Using …

Accurate prediction of micro-p K a values is crucial for understanding and modulating the
acidity and basicity of organic molecules, with applications in drug discovery, materials …

Sentiment analysis is a common and challenging task in natural language processing
(NLP). It is a widely studied area of research; it facilitates capturing public opinions about a …

Isolating the features associated with different materials growth conditions is important to
facilitate the tuning of these conditions for effective materials growth and characterization …

The molecular mechanisms of olfaction, or the sense of smell, are relatively underexplored
compared with other sensory systems, primarily because of its underlying molecular …

Background Deep learning methods are increasingly applied in the medical field; however,
their lack of interpretability remains a challenge. Captum is a tool that can be used to …

Functional heterogeneity of healthy human tissues complicates interpretation of molecular
studies, impeding precision therapeutic target identification and treatment. Considering this …

This study proposes a method for predicting three-dimensional (3D) local strain distribution
under compressive deformation of as-cast Mg/LPSO two-phase alloys from 3D …

Catalyst screening is a critical step in the discovery and development of heterogeneous
catalysts, which are vital for a wide range of chemical processes. In recent years …