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The benefits of medical AI assistance vary based on user expertise

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A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis.A new study by researchers at MIT and elsewhere found that, while AI assistance generally improved the accuracy of non-experts and clinicians in diagnosing skin diseases, AI explainability methods had different impacts depending on the users’ knowledge […]

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How a medical database developed at MIT evolved into a global standard of data-sharing

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Before the advancement of scientific data storage and collaboration via the cloud, medical investigators seeking health research breakthroughs had to overcome significant obstacles to collaboration and key clinical data gathering. Data were siloed and difficult to distribute, so those looking to undertake research had no option but to gather them themselves. This not only made research

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When silence is safer: a review and decision-theoretic framework for LLM abstention in healthcare

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Large language models (LLMs) are designed to generate answers to user prompts, which often drives them to respond even when uncertainty is high, information is incomplete, or a refusal would be more appropriate. In healthcare, this tendency can be dangerous: confidently stated but inaccurate medical advice can cause significant harm, making the ability to abstain

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Advancing regulatory variant effect prediction with AlphaGenome

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🔘 Paper page: nature.com/articles/s41586-025-10014-0 Abstract Deep learning models that predict functional genomic measurements from DNA sequences are powerful tools for deciphering the genetic regulatory code. Existing methods involve a trade-off between input sequence length and prediction resolution, thereby limiting their modality scope and performance1,2,3,4,5. We present AlphaGenome, a unified DNA sequence model, which takes as

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AWS GraphRAG deployment cuts drug research cycles by 87%

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A recent AWS GraphRAG deployment reduced drug research and development cycles in pharmaceutical environments by 87 percent. This acceleration is achieved by integrating previously separated proprietary databases into a unified and queryable knowledge graph. Historically, initial data gathering and screening phases took over six months per iteration, yielding a low five percent success rate. Crucial

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One in seven prefer consulting AI chatbots to seeing a doctor, UK study shows

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Exclusive: Doctors say ‘highly concerning’ poll highlights risk to patients of turning to AI for medical adviceOne in seven people are using AI chatbots for health advice instead of seeing their GP, a UK study has found.The poll of more than 2,000 people found that – of the 15% turning to chatbots – one in

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How to create “humble” AI

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Artificial intelligence holds promise for helping doctors diagnose patients and personalize treatment options. However, an international group of scientists led by MIT cautions that AI systems, as currently designed, carry the risk of steering doctors in the wrong direction because they may overconfidently make incorrect decisions.One way to prevent these mistakes is to program AI

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How AI is Reducing Emergency Room Overcrowding

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Emergency room overcrowding has become one of healthcare’s most pressing challenges, putting countless lives at risk through delayed care and strained resources. The scale of this crisis is stark: over 1.5 million patients experienced wait times exceeding 12 hours in major emergency departments in 2023, with 65% of these cases involving patients awaiting admission. Among

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Top 10+ Mental Health Apps for 24/7 Emotional Support

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In a world where nearly 1 billion people struggle with mental health challenges, yet 61% don’t seek traditional treatment, digital solutions are becoming increasingly vital. From AI-powered therapy companions to professional teletherapy platforms, mental health apps are breaking down barriers of cost, accessibility, and stigma. But with hundreds of options available – from meditation guides

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EU AI Act in Healthcare: 15 Steps to Ensure Your Company’s Compliance

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The European Union’s Artificial Intelligence Act, which came into effect on August 1, 2024, has ushered in a new era of AI regulation with global implications. This groundbreaking legislation extends its reach beyond European borders, affecting all entities utilizing AI technology that impacts EU citizens or employees – regardless of the company’s physical location. The

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