Volume 28, Issue 3 (September 2024)                   Physiol Pharmacol 2024, 28(3): 257-270 | Back to browse issues page

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Gudadappanavar A, Hombal P, Benni J. An Evidence-Based Systematic Review: The Impact of Artificial Intelligence in Pharmacology and Health Research. Physiol Pharmacol 2024; 28 (3) : 3
URL: http://ppj.phypha.ir/article-1-2189-en.html
An Evidence-Based Systematic Review: The Impact of Artificial Intelligence in Pharmacology and Health Research
Anupama Gudadappanavar , Prashant Hombal , Jyoti Benni
Abstract:   (1303 Views)

Introduction: Artificial intelligence (AI) has gradually become a vital part of health care currently. AI and machine learning (ML) have made significant progress in recent years, particularly in terms of deep learning (DL) approaches in pharmacology. AI will have a significant impact on pharmacologists at all levels in the coming decade, including drug development and research, medical education, and clinical practice. AI is transforming health research, by boosting data analysis, providing diagnostic tools, predicting outcomes, and helping develop personalized treatments. AI affords early detection of diseases and creates virtual patient models to assess treatments. In this reverence, the objective of this systematic review is to evaluate the impact of AI in the field of Pharmacology and health research. 
Methods: The review was performed by preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The studies published from 2009 to 2022 were identified using specific keywords through searches on PubMed, Google Scholar, Web of Science, Science Direct, and Cochrane review databases. The explorations retrieved 972 studies and on subsequent screening with the inclusion and exclusion criteria, 71 studies were included for this systematic review.
Results: The collective results showed that AI plays a significant role in the fields of pharmacology, research, medical education, health care diagnostics, and clinical practice, with high accuracy and efficiency.
Conclusion: AI has emerged as a powerful tool in pharmacology and healthcare, offering innovative solutions to longstanding challenges. It has revolutionized and digitally transformed the manual healthcare system into an automated version in many areas.

Article number: 3
Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Pharmacology, Health Research
Full-Text [PDF 868 kb]   (171 Downloads)    
Type of Manuscript: Review | Subject: Clinical Physiology/Pharmacology
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