Nov 22, 2024
Proofig AI's founder, Dr. Dror Kolodkin-Gal, highlights the risks of image integrity issues, including unintentional duplications, and how AI-powered image proofing software can help researchers, universities, and publishers proactively detect problems before publication.
Clinical research is the foundation upon which breakthroughs in medical devices and pharmaceuticals are built. To bring a novel therapy to market, researchers must write and publish sufficient evidence proving that the product meets its intended purpose. This requires collecting and sharing data from multiple sources, such as literature searches, statistics from clinical trials, images, and more.
The evidence shared in clinical research must be accurate, or the consequences can be severe. In 2022, a six-month investigation called into question the validity of results in an integral study of Alzheimer’s disease conducted in 20061. Investigators suspect that some of the figures included in the paper were fabricated, undermining the core findings linking a specific amyloid-β protein assembly to Alzheimer’s disease with neurodegeneration.
The study established the dominant amyloid hypothesis of Alzheimer’s, suggesting that the primary cause of the disease is the accumulation of Aβ clumps, known as plaques, in brain tissue. As this hypothesis became more widespread, many researchers developed drugs to combat amyloid formation in patients’ brains.
According to Science2, the investigator “identified apparently altered or duplicated images in dozens of journal articles,” all of which were attributed to the author of the study in question. Some Alzheimer’s experts now suspect that studies from this researcher have misdirected Alzheimer’s research for 16 years and potential loses of hundreds of millions of dollars.
This incident highlights the potential damage that can come from not being able to recognise images with issues before publication. While intentional misconduct is a rare occurrence in scientific publishing and very hard to determine for sure, including image issues unintentionally is a very common phenomenon that can still fundamentally damage all parties involved, as well as damage research in general.
The issue with images
Researchers have multiple resources at their disposal to proactively check written content. They can use software to check for readability, grammatical issues, plagiarism, and more to remove issues in the text and increase their chances of publication. Unfortunately, a lack of tools to proactively check for image integrity issues means that they are prevalent in publishing. According to leading image data integrity analyst Jana Christopher MA, the percentage of manuscripts flagged for image related problems ranges from 20 to 35 per cent3.
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