Artificial Intelligence Medical Compendium

BACKGROUND: The past decade has been marked by the progressive integration of artificial intelligence (AI), especially in the form of machine learning and deep learning. Pediatric orthopaedics remains an underexplored area in AI, especially in the co... read more 

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Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modeling. A powerful and widely used approach can be understood as a discretization of the histogram of pai... read more 

We present WEST, an open-source plane-wave pseudopotential code for large-scale excited-state materials simulations, and describe its theoretical foundations, software architecture, and capabilities. WEST implements full-frequency GW, quantum defect ... read more 

Polynomial machine learning potentials (MLPs) based on polynomial rotational invariants have been systematically developed for various systems and applied to efficiently predict crystal structures. In this study, we propose a methodology founded on p... read more 

To date the environmental impacts of production of most chemicals are unknown, hindering sustainable process evaluation and design. Life cycle assessment (LCA) is the most comprehensive method for estimating these environmental impacts but existing L... read more 

The concept of "undruggable" targets has long represented a major limitation in medicinal chemistry, referring to proteins and biomolecules that lack well-defined binding pockets or exhibit highly dynamic conformational behavior. However, advances in... read more 

The electrochemical hydrogen evolution reaction (HER) in overall water splitting is one of the core technological pathways for green hydrogen production. Developing nonprecious metal electrocatalysts with high activity, low cost, and earth abundance ... read more 

Abundant experimental data support the view that motion detection is a canonical neural operation, common to a wide variety of species and different stages in the visual stream. However, existing motion models lack this generality, as their predictiv... read more 

Pathology foundation models (PFMs) are expected to represent the same tissue in the same way on any scanner, but their embeddings still carry scanner signals. Scanner-related image differences and the scanner sensitivity of PFMs have each been descri... read more