Health
Study Finds AI Models Fall Short in Early Medical Diagnosis
A new study has found that artificial intelligence language models still struggle with one of the most critical aspects of medical care, raising concerns about their use without human oversight.
Researchers from Mass General Brigham reported that AI systems failed to produce an appropriate early diagnosis more than 80 per cent of the time. The findings, published in JAMA Network Open, highlight ongoing limitations in how these systems reason through complex clinical scenarios.
The study examined 21 large language models, including systems developed by OpenAI, Google and xAI. Among those tested were versions of GPT, Gemini, Claude, Grok and DeepSeek.
Researchers used a structured evaluation tool known as PrIME-LLM to assess how well the models handled different stages of clinical reasoning. These stages included forming an initial diagnosis, ordering tests, reaching a final diagnosis and planning treatment. The models were tested using 29 standardised clinical scenarios, with information introduced gradually to mirror real-life patient cases.
While the systems showed relatively strong performance when identifying a final diagnosis, their ability to generate a differential diagnosis — a key step in distinguishing between conditions with similar symptoms — remained limited. This early-stage reasoning is widely regarded as essential in medical decision-making.
Marc Succi, a co-author of the study, said current models are not ready for independent clinical use. He noted that differential diagnosis represents a core part of medical practice that AI has yet to replicate effectively.
Another researcher, Arya Rao, said the findings show that AI performs best when given complete information but struggles when cases are still developing. She explained that the models are less reliable in situations where doctors must make judgments based on limited or uncertain data.
Despite these shortcomings, the study identified a group of higher-performing systems, including advanced versions of GPT, Gemini, Claude and Grok. These models achieved final diagnosis success rates ranging from around 60 per cent to over 90 per cent when provided with detailed clinical data such as lab results and imaging.
Experts not involved in the research also stressed the importance of caution. Susana Manso García said the findings reinforce that AI should not replace professional medical judgement. She advised that patients continue to seek guidance from qualified healthcare providers when dealing with health concerns.
The study concludes that while AI has made progress, it still requires close human supervision in clinical settings. Researchers say the technology shows promise as a support tool, but its current limitations mean it cannot yet be trusted to make independent medical decisions.
Health
Global Mental Health Cases Near 1.2 Billion as Anxiety and Depression Drive Sharp Worldwide Rise
A major global analysis has found that mental health conditions have surged to an estimated 1.2 billion people worldwide, driven largely by steep increases in anxiety and depression over the past three decades.
The findings, published in The Lancet as part of the Global Burden of Disease Study 2023, show that the number of people living with mental disorders has almost doubled since 1990, marking a 95% rise. Researchers say major depressive disorder and anxiety disorders have seen even sharper growth, increasing by 131% and 158% respectively, making them the most prevalent mental health conditions globally.
The report describes mental illnesses as widespread conditions that create long-term disability and significant human suffering. It also highlights broader consequences for economies and public services, including reduced productivity, lower workforce participation and increasing pressure on health and welfare systems.
Researchers estimate that in 2023 alone, around 620 million females and 552 million males were affected by mental health conditions. While the overall burden is rising across both sexes, the study points to notable differences in the types and prevalence of disorders.
Among women, depression and anxiety were the most commonly reported conditions, alongside higher rates of eating disorders such as anorexia nervosa and bulimia nervosa. The report links this disparity to a mix of biological, social and structural factors, including exposure to domestic violence, sexual abuse, gender inequality and reproductive health-related changes.
In contrast, neurodevelopmental and behavioural disorders, including attention deficit hyperactivity disorder (ADHD), conduct disorder and autism spectrum conditions, were more frequently diagnosed in men.
Teenagers aged 15 to 19 were identified as the group experiencing the highest mental health burden globally, raising concerns about early onset of conditions and insufficient preventive care for young people.
The study identifies several key risk factors associated with mental illness, including childhood sexual violence, bullying and intimate partner violence. These factors are strongly linked to conditions such as depression, schizophrenia, bipolar disorder and anxiety disorders. However, researchers note that such exposures have remained relatively stable over time and account for only a portion of the overall rise.
According to the authors, broader drivers are likely contributing to the increasing prevalence of mental disorders. These include genetic and biological influences, poverty, inequality, and the growing impact of global crises such as armed conflict, pandemics, natural disasters and climate-related stress.
While mental health conditions have long been a leading cause of disability worldwide, the report warns that the situation is worsening. At the same time, health systems have not expanded services at a pace matching demand.
The authors caution that the gap between rising need and limited access to care is becoming more pronounced, leaving millions without adequate treatment or support.
Health
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Health
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