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Artificial intelligence and machine learning for clinical pharmacology.
Ryan, David K; Maclean, Rory H; Balston, Alfred; Scourfield, Andrew; Shah, Anoop D; Ross, Jack.
Afiliação
  • Ryan DK; Department of Clinical Pharmacology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Maclean RH; Department of Clinical Pharmacology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Balston A; Institute of Health Informatics, University College London, London, UK.
  • Scourfield A; Department of Clinical Pharmacology, Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Shah AD; Department of Clinical Pharmacology, University College London Hospitals NHS Foundation Trust, London, UK.
  • Ross J; Department of Clinical Pharmacology, University College London Hospitals NHS Foundation Trust, London, UK.
Br J Clin Pharmacol ; 90(3): 629-639, 2024 03.
Article em En | MEDLINE | ID: mdl-37845024
Artificial intelligence (AI) will impact many aspects of clinical pharmacology, including drug discovery and development, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation in clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacologia Clínica / Inteligência Artificial Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacologia Clínica / Inteligência Artificial Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article