人工智能对未来临床药学研究和学术的影响

IF 1.3 Q4 PHARMACOLOGY & PHARMACY
Alexandre Chan Pharm.D., MPH, FCCP, William L. Baker Pharm.D., MPH, FCCP, Daniel Abazia Pharm.D., Jerry Bauman Pharm.D., FCCP, C. Lindsay DeVane Pharm.D., FCCP, Kellie J. Goodlet Pharm.D., Natalie Hall Pharm.D., James Kevin Hicks Pharm.D., PhD, FCCP, Ellen Jones Pharm.D., Chi-Hua Lu Pharm.D., Donald C. Moore Pharm.D., FCCP, Nicholas R. Nelson Pharm.D., Kaylee Putney Pharm.D., MBA, Aracely Sosa Pharm.D., Toby Trujillo Pharm.D., FCCP, Crystal Zhou Pharm.D
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引用次数: 0

摘要

现代生物医学研究的几乎每个方面都涉及人工智能(AI)。这篇ACCP评论预测了人工智能在临床药学研究和学术中的作用。在科学方法的各个阶段回顾了人工智能的潜在好处/机会以及局限性/挑战,包括:(1)提出研究问题、研究设计和执行;(2)数据分析;(3)临床药学研究的报道与传播。人工智能在临床药学研究中的好处和机遇包括简化假设生成和促进研究设计,克服传统统计分析技术的局限性,促进稿件开发和传播,加快同行评审。人工智能的局限性和挑战包括在受试者招募中引入偏见;产生虚假信息,也被称为“人工智能幻觉”;对难以验证的“黑盒”分析的关注;潜在的法律责任;缺乏问责;调查人员需要确保人工智能生成内容的准确性和完整性。总之,人工智能能力的快速发展具有巨大的潜力,可以彻底改变和加速临床药学研究和学术研究;然而,也必须认识到并减轻人工智能带来的挑战和限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of artificial intelligence on future clinical pharmacy research and scholarship

Impact of artificial intelligence on future clinical pharmacy research and scholarship

Almost every facet of modern biomedical research involves artificial intelligence (AI). This ACCP commentary forecasts the role of AI in clinical pharmacy research and scholarship. The potential benefits/opportunities together with the limitations/challenges of AI are reviewed for stages of the scientific method including (1) developing the research question(s), study design, and execution; (2) data analysis; and (3) reporting and dissemination of clinical pharmacy research. Benefits and opportunities of AI in clinical pharmacy research include streamlining hypothesis generation and facilitating study design, overcoming limitations of traditional statistical analysis techniques, facilitating manuscript development and dissemination, and expediting peer review. Limitations and challenges of AI include the introduction of biases in subject recruitment; generation of false information, also known as “AI hallucinations”; concern of “black box” analyses that are difficult to validate; potential legal liabilities; lack of accountability; and the need for investigators to ensure the accuracy and integrity of AI-generated content. In summary, rapid progress of AI capabilities has great potential to revolutionize and accelerate clinical pharmacy research and scholarship; however, it is also imperative to recognize and mitigate the challenges and limitations introduced by AI.

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CiteScore
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