Fraud in Medical Publications

: 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.