The potential and pitfalls of artificial intelligence in clinical pharmacology-Reference-Cited by-同舟云学术

The potential and pitfalls of artificial intelligence in clinical pharmacology

Published:2023-01-30 Issue:3 Volume:12 Page:279-284
ISSN:2163-8306
Container-title:CPT: Pharmacometrics & Systems Pharmacology
language:en
Short-container-title:CPT Pharmacom & Syst Pharma

Author:

Johnson Martin¹,Patel Mishal²,Phipps Alex¹,van der Schaar Mihaela³,Boulton Dave⁴,Gibbs Megan⁴

Affiliation:

1. Clinical Pharmacology and Quantitative Pharmacology Clinical Pharmacology and Safety Science, R&D, AstraZeneca Cambridge UK

2. Clinical Pharmacology and Quantitative Pharmacology Artificial Intelligence & Data Analytics, R&D, AstraZeneca Cambridge UK

3. Cambridge Centre for Artificial Intelligence in Medicine, Department of Applied Mathematics and Theoretical Physics and Department of Population Health University of Cambridge Cambridge UK

4. Clinical Pharmacology and Quantitative Pharmacology Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca Gaithersburg Maryland USA

Publisher

Wiley

Subject

Pharmacology (medical),Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/psp4.12902

Reference10 articles.

1. From Real‐World Patient Data to Individualized Treatment Effects Using Machine Learning: Current and Future Methods to Address Underlying Challenges

2. Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records

3. Deep learning improves prediction of drug–drug and drug–food interactions

4. Drug-Drug Interaction Prediction on a Biomedical Literature Knowledge Graph

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