Revealing the Paper Mill Iceberg: AI-Based Screening of Cancer Research Publications.

Paper mills are fraudulent organisations that publish fake manuscripts for profit. Paper mill-supported papers have been identified in the cancer research literature, where some papers show features of template use, with seemingly pre-formulated sentences. We trained a machine learning model to distinguish between paper mill papers and genuine cancer research papers published between 1999 and 2024. Using titles and abstracts, the model achieved a prediction accuracy of 0.91. When applied to the cancer research literature, it flagged 9.87% (95% CI 9.83 to 9.90) of papers and revealed a large increase in flagged papers from 1999 to 2024, both across the entire corpus and in the top 10% of journals by impact factor. Most publishers had substantial numbers of flagged papers. Over 170,000 papers by authors from Chinese institutions were flagged. These results indicate that paper mills are a large and growing problem in the cancer literature and are not restricted to low-impact journals.