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AI and machine learning for clinical pharmacology: A Primer
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Artificial intelligence (AI) will impact many aspects of clinical
pharmacology including drug discovery and development, clinical trials,
personalised 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 into 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.
Title: AI and machine learning for clinical pharmacology: A Primer
Description:
Artificial intelligence (AI) will impact many aspects of clinical
pharmacology including drug discovery and development, clinical trials,
personalised 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 into 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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