Although substantial efforts have been made using graph neural networks (GNNs) for artificial intelligence (AI)-driven drug discovery, effective molecular representation learning remains an open challenge, especially in the case of insufficient label...
Today, pharmaceutical industry faces great pressure to employ more efficient and systematic ways in drug discovery and development process. However, conventional formulation studies still strongly rely on personal experiences by trial-and-error exper...
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Nov 20, 2023
OBJECTIVE: In this study, we used artificial intelligence (AI) technology to explore for automated medical record quality control methods, standardize the process for medical record documentation, and deal with the drawbacks of manually implemented q...
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological res...
Journal of the American Medical Informatics Association : JAMIA
Nov 17, 2023
OBJECTIVE: To describe and appraise the use of artificial intelligence (AI) techniques that can cope with longitudinal data from electronic health records (EHRs) to predict health-related outcomes.
Applying artificial intelligence (AI) to cancer care has the potential to transform and enhance nursing practice and patient outcomes, from cancer prevention and screening through treatment, survivorship, and end-of-life care.
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