A powerful new AI tool has uncovered what could be one of the biggest integrity problems in modern science — more than 250,000 cancer research papers may be fake.
The study, published in The BMJ and led by Professor Adrian Barnett from Queensland University of Technology (QUT), examined 2.6 million cancer research papers published between 1999 and 2024. Researchers found that more than 250,000 papers contained writing patterns similar to studies already retracted over suspected fabrication by fraudulent "paper mills."
Paper mills are companies that sell fake or low-quality scientific studies, including authorship positions and complete ready-made papers. These studies may contain reused text, unusual or awkward language, and fabricated data or images.
The team trained a language model called BERT to identify subtle textual "fingerprints" that repeatedly appear in known paper mill products. When evaluated using verified examples, the model correctly detected suspicious papers 91 percent of the time.
Key findings from the analysis: - Suspicious papers rose sharply over two decades, from about 1% in the early 2000s to a peak of more than 16% in 2022. - The problem appears across thousands of journals from major publishers, including those with strong reputations. - Suspicious papers were especially common in molecular cancer biology and early-stage lab research. - Certain cancer types — gastric, liver, bone and lung cancer — had particularly high rates of flagged studies.
"Cancer research influences clinical trials, drug development and patient care. If fabricated studies make their way into the evidence base, they can mislead real scientists and ultimately slow progress for patients," Professor Barnett said.
Three scientific journals are already testing the system as part of their editorial review process. The researchers also plan to adapt the tool for other scientific fields.
The team emphasized that flagged papers should not automatically be treated as fraudulent — the results are warning signals requiring human expert review.




