Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the ...

A study reveals machine learning algorithms can predict compressive strength in concrete with waste glass powder, enhancing ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...

However, machine learning (ML) offers hope in this situation because it excels at prediction and analysis. In this paper, we proposed nine ML approaches, such as K-nearest neighbors (KNN), support ...