AI flags more than 250,000 suspicious cancer research papers
An international research team has used a machine learning model called BERT to identify over 250,000 potentially fraudulent cancer research papers linked to 'paper mills.' These companies mass-produce low-quality or fabricated studies, which the AI detects by analyzing recurring textual patterns.
Why it matters
The proliferation of fake research undermines scientific integrity and public trust in medical literature, making automated detection tools essential for academic publishing.
A new machine learning system has flagged more than 250,000 cancer research papers that may be connected to so called "paper mills."
The study, published in The BMJ , examined 2.6 million cancer research papers released between 1999 and 2024. It was led by QUT researcher Professor Adrian Barnett, from the School of Public Health and Social Work and Australian Centre for Health Services and Innovation (AusHSI), together with an international group of collaborators.
The researchers found that more than 250,000 papers contained writing patterns similar to those seen in studies that had already been retracted over suspected fabrication.
"Paper mills are companies that sell fake or low-quality scientific studies. They are producing 'research' on an industrial scale, and our findings suggest the problem in cancer research is far larger than most people realized," Professor Barnett said.
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