Department of Anesthesiology, Critical Care and Pain Medicine, Policlinico Umberto I, "Sapienza" University of Rome, Rome 00185, Italy.
Department of Anesthesiology, Critical Care and Pain Medicine, Policlinico Umberto I, "Sapienza" University of Rome, Rome 00185, Italy.
Anesthesiol Clin. 2024 Dec;42(4):607-616. doi: 10.1016/j.anclin.2024.02.004. Epub 2024 Mar 15.
This review highlights the increasing prevalence of fraudulent data and publications in medical research, emphasizing the potential harm to patients and the erosion of trust in the medical community. It discusses the impact of low-quality studies on clinical guidelines and patient safety, emphasizing the need for prompt identification. The review proposes using machine learning and artificial intelligence as potential tools to detect anomalies, plagiarism, and data manipulation, potentially improving the peer review process. Despite the acknowledgment of this problem and the growing number of retractions, the review notes a lack of focus on the clinical implications of forged evidence.
这篇综述强调了医学研究中伪造数据和出版物日益增多的现象，指出这可能对患者造成危害，并破坏医疗界的信任。文中讨论了低质量研究对临床指南和患者安全的影响，强调了及时发现这些问题的必要性。该综述提出使用机器学习和人工智能作为潜在工具来检测异常、抄袭和数据操纵，这可能有助于改进同行评审过程。尽管人们已经认识到这个问题的存在，并且被撤回的论文数量也在不断增加，但该综述指出，人们对伪造证据的临床影响仍关注不足。
