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Study Finds AI Systems Can Repeat Fake Medical Claims When Framed Credibly

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“Large language models accept fake medical claims if presented as realistic in medical notes and social media discussions, a study has found.”

As more people turn to the internet to research symptoms, compare treatments and share personal health experiences, artificial intelligence tools are increasingly being used to answer medical questions. A new study warns that many of these systems remain vulnerable to medical misinformation, particularly when false claims are presented in authoritative or realistic language.

The findings, published in The Lancet Digital Health, show that leading artificial intelligence systems can mistakenly repeat incorrect medical information when it appears in formats that resemble professional healthcare documents or trusted online discussions. Researchers analysed how large language models respond when faced with false medical statements written in a credible tone.

The study examined responses from 20 widely used language models, including systems developed by OpenAI, Meta, Google, Microsoft, Alibaba and Mistral AI, as well as several models specifically fine-tuned for medical use. In total, researchers assessed more than one million prompts designed to test whether AI would accept or reject fabricated health information.

Fake statements were inserted into real hospital discharge notes, drawn from common health myths shared on Reddit, or embedded in simulated clinical scenarios written to resemble authentic healthcare guidance. Across all models tested, incorrect information was accepted around 32 percent of the time. Performance varied significantly, with smaller or less advanced models accepting false claims in more than 60 percent of cases, while more advanced systems, including ChatGPT-4o, did so in roughly 10 percent of responses.

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The researchers also found that medical fine-tuned models performed worse than general-purpose systems, raising concerns about tools designed specifically for healthcare use.

“Our findings show that current AI systems can treat confident medical language as true by default, even when it’s clearly wrong,” said Eyal Klang of the Icahn School of Medicine at Mount Sinai, one of the study’s senior authors. He added that how a claim is written often matters more to the model than whether it is accurate.

Some of the accepted misinformation could pose real risks to patients. Several models endorsed claims such as Tylenol causing autism during pregnancy, rectal garlic boosting immunity, mammograms causing cancer, and tomatoes thinning blood as effectively as prescription medication. In another case, a discharge note incorrectly advised patients with oesophageal bleeding to drink cold milk, which some models repeated without flagging safety concerns.

The study also tested how AI systems responded to flawed arguments known as fallacies. While many fallacies prompted scepticism, models were more likely to accept false claims framed as expert opinions or warnings of catastrophic outcomes.

Researchers say future work should focus on measuring how often AI systems pass on falsehoods before they are used in clinical settings. Mahmud Omar, the study’s first author, said the dataset could help developers and hospitals stress-test AI tools and track improvements over time.

The authors said stronger safeguards will be essential as AI becomes more deeply embedded in healthcare decision-making.

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AI Model Surpasses Doctors in Key Medical Decision Tests, Study Finds

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A new study by researchers at Harvard Medical School and Beth Israel Deaconess Medical Center has found that advanced artificial intelligence systems can outperform human doctors in several medical reasoning tasks, including diagnosis and emergency care decisions.

The research compared physicians with large language models across a range of clinical scenarios. According to the findings, AI systems showed stronger performance in tasks such as identifying likely diagnoses, recommending treatment steps, and making decisions in emergency department settings where information is often limited.

Arjun Manrai, a co-senior author of the study, said the results demonstrate the rapid progress of AI in healthcare. He noted that the model surpassed both earlier systems and physician benchmarks in most tests. At the same time, he cautioned that better performance in controlled settings does not guarantee improved outcomes in real-world care.

The study evaluated OpenAI’s reasoning model, released in 2024, using a mix of published clinical cases and real-world emergency department data. Researchers presented the system with patient scenarios at different stages of care, from initial triage to later admission decisions. At each step, the AI was given only the information available at that point and asked to suggest diagnoses and next actions.

The results showed that the AI consistently outperformed doctors, especially in areas requiring structured reasoning and documentation. The largest gap appeared during the triage stage, when limited information makes decision-making more difficult. As additional data became available, both AI and physicians improved in accuracy, though the AI maintained an edge in many cases.

Peter Brodeur, a co-author of the study, said traditional testing methods such as multiple-choice questions are no longer sufficient to measure progress, as many AI models now achieve near-perfect scores. He added that newer evaluation approaches are needed to track further advances.

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Despite the promising results, researchers stressed that the use of AI in healthcare must be approached carefully. They warned that while a model may correctly identify a diagnosis, it could also recommend unnecessary tests or interventions that might carry risks for patients.

The study’s authors called for further trials in real clinical environments to better understand how AI tools perform in practice. They also highlighted the need for investment in infrastructure and clear frameworks to support the safe use of such technologies.

The findings come with some limitations, as the analysis focused on a specific version of the AI model, which has since been updated. Researchers said additional studies are needed to compare different systems and explore how doctors and AI can work together effectively in patient care.

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New Study Reveals How Coffee May Help Protect the Body From Ageing

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A new study has uncovered a key biological mechanism that may explain why coffee has long been linked to healthier ageing and a lower risk of chronic disease.

Researchers at Texas A&M College of Veterinary Medicine & Biomedical Sciences found that compounds in coffee interact with a protein in the body known as NR4A1, a receptor involved in regulating stress responses, inflammation and cellular repair. The findings shed new light on how coffee may help protect the body from age-related decline.

For years, studies have associated regular coffee consumption with a longer life and reduced risk of conditions such as heart disease, cancer and cognitive decline. Until now, however, the biological processes behind those benefits have remained largely unclear.

The research team identified NR4A1 as a critical target for several naturally occurring compounds in coffee, particularly polyphenols and other polyhydroxylated substances. These compounds bind to the receptor and appear to influence how it functions.

NR4A1 acts as what scientists call a nutrient sensor, responding to dietary compounds and helping the body adapt to stress and damage. It plays an important role in controlling inflammation, maintaining energy balance and promoting tissue repair — all essential processes in healthy ageing.

Stephen Safe, one of the study’s lead researchers, said the findings provide a clearer understanding of coffee’s protective effects. He explained that NR4A1 helps limit damage when tissues are under stress, and that its absence can worsen the effects of injury or disease.

Laboratory tests showed that coffee compounds reduced cellular damage and slowed the growth of cancer cells. When researchers removed NR4A1 from the cells, those benefits disappeared, strongly suggesting that the receptor is central to coffee’s protective action.

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The study also highlights that coffee’s health effects are likely driven by more than caffeine alone. Decaffeinated coffee has also been linked to improvements in learning and memory, indicating that other components, including polyphenols, may play a significant role.

Recent research has suggested that moderate consumption of caffeinated coffee may also reduce anxiety, improve attention and vigilance, and lower levels of inflammation.

Scientists caution that while the findings are promising, more research is needed to determine how significant the NR4A1 pathway is in humans and how it interacts with other biological systems.

Still, the discovery offers an important step toward understanding why coffee remains one of the most widely studied beverages in nutrition science. It also reinforces the idea that compounds found in everyday foods and drinks can play a meaningful role in supporting long-term health and resilience as people age.

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Study Finds Rise in 11 Cancers Among Younger Adults in England

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A major study has found that rates of 11 types of cancer are increasing among younger adults in England, raising fresh concerns among researchers about factors driving the trend.

The study, conducted by the Institute of Cancer Research and Imperial College London, examined cancer diagnoses between 2001 and 2019 in adults aged 20 to 49. It identified rising incidence in a range of cancers, including breast, colorectal, pancreatic and kidney cancers.

The full list includes breast, colorectal, pancreatic, kidney, liver, gallbladder, thyroid, ovarian and endometrial cancers, as well as oral cancer and multiple myeloma, a form of blood cancer.

Researchers noted that for most of these cancers, rates have also increased among older adults, where cancer remains far more common. This suggests that some shared risk factors may be affecting multiple age groups.

Two cancers, however, stood out. Rates of colorectal and ovarian cancer rose only among younger adults, pointing to possible age-specific causes that are not yet fully understood.

Scientists examined a range of established cancer risk factors, including smoking, alcohol consumption, diet, physical activity and body weight. While these factors are known to contribute significantly to cancer risk, they do not appear to fully explain the recent rise in cases among younger people.

In fact, many of these traditional risk factors have either remained stable or improved over recent decades. Smoking rates have declined, alcohol consumption has generally fallen or levelled off, physical inactivity has decreased, and intake of red and processed meat has dropped.

Obesity was the notable exception. Rates of obesity have risen steadily across all adult age groups and remain a significant contributor to cancer risk. Even so, researchers found that obesity alone could not account for the broader increase in cancer diagnoses among younger adults.

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This was particularly true for cancers commonly associated with excess body weight, such as bowel, kidney, pancreatic, liver, gallbladder and endometrial cancers. While rising obesity may be playing a role, it does not fully explain the trend.

The findings suggest that other factors may be contributing. Researchers say further investigation is urgently needed into possible causes, including environmental exposures, changes in diet or lifestyle during childhood, and other early-life influences.

They also pointed to the possibility that improved diagnostic tools, increased screening and greater public awareness may be leading to more cases being detected.

Public health experts say the study highlights the need for continued prevention efforts, particularly in tackling smoking and obesity, which remain more common in disadvantaged communities. As researchers work to better understand the causes, the rise in cancer among younger adults is likely to remain an important area of focus for health authorities.

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