Editorial: Machine learning advancements in pharmacology: transforming drug discovery and healthcare.
Frontiers in pharmacology, ISSN: 1663-9812, Vol: 16, Page: 1583486
2025
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
"In recent years, the integration of machine learning (ML) into pharmacology has revolutionized how we approach drug discovery, disease modeling, and therapeutic development. By leveraging vast datasets and computational power, ML has enabled researchers to uncover patterns, predict outcomes, and accelerate drug development processes that were previously unimaginable. This Research Topic on 'Machine Learning Advancements in Pharmacology' features five impactful studies that highlight the diverse applications and potential of ML in this field. These contributions, encompassing original research and a systematic review, exemplify the transformative role of ML in addressing some of the most pressing challenges in pharmacology."
Bibliographic Details
http://dx.doi.org/10.3389/fphar.2025.1583486; http://www.ncbi.nlm.nih.gov/pubmed/40124782; https://www.frontiersin.org/articles/10.3389/fphar.2025.1583486/full; https://digitalcommons.chapman.edu/pharmacy_articles/1113; https://digitalcommons.chapman.edu/cgi/viewcontent.cgi?article=2114&context=pharmacy_articles
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