Large language models (LLMs) are now routinely used to write clinical notes, discharge summaries, referral letters, patient instructions and insurance correspondence. Their appeal is obvious: they are fast, fluent and usually accurate. As the documentation burden increases and clinical time shrinks, AI-generated text is becoming embedded in everyday clinical workflows. The dominant safety response has …
Editorials urge clinicians and researchers to speak out against misinformation. Public health leaders warn that trust in evidence-based guidance is declining. Scientists describe being “under attack for someone else’s political gain.” These pleas, warnings, repetitions of scientific facts, and proclamations of authority in response to misinformation and conspiracy beliefs are welcome but ineffective. It’s more …
Development of artificial intelligence (AI) is moving along two distinct paths. The last decade has been centred on large language models (LLM) that generate fluent text by predicting the next word in a sequence. A newer approach focuses on building world models – systems that learn how the physical world behaves and changes over time. …
World models and word models: layers of the AI cake Read More »
Lessons from the global leader in water management South Africa’s Constitution guarantees the right to sufficient water. Water is recognised as a condition of dignity, health, and citizenship, and the state is obliged to take reasonable measures to realise that right. Constitutions do not pump water. When water systems fail, consequences for healthcare are immediate. Maternity …
Constitutions don’t pump water: why healthcare needs a water strategy Read More »
Intraoperative EEG-guided depth of anaesthesia monitoring may reduce postoperative complications such as delirium, but the evidence is mixed. This uncertainty is a useful lens for seeing how clinical evidence is produced, evaluated and trusted. A brief report We examined the association between intraoperative EEG-based depth of anaesthesia (DoA) guidance and postoperative delirium in a retrospective …
Plausibility is not proof: what two studies reveal about trust in clinical research Read More »
Artificial intelligence (AI) is a set of technologies that will profoundly impact healthcare in all dimensions of quality. At times, however, the AI industry and the community of healthcare quality specialists talk past each other. This is because they operate with different epistemologies – the term for descriptions about what we treat as knowledge, how …
Diagnosis is an act of naming: the point at which we are told what kind of health problem we’re dealing with. With a successful diagnosis, uncertainty ends, explanation is offered and appropriate treatment can start. From a biological point of view, however, diagnosis arrives late. By the time a condition like type 2 diabetes is …
The paradox of precision medicine: does disease disappear? Read More »
Albert Invent is a new software platform for chemists and materials scientists – the people who combine substances in the lab to make products for the modern world. The company doesn’t disclose who or what it is named after. Albert Einstein seems the reasonable guess. But an even better fit is someone further back in …
It’s common for private doctors in Mexico City, and across Latin America, to wake up each morning and be greeted by 100 or more WhatsApp messages. The messages typically contain urgent clinical concerns mixed with routine administrative requests. Often, no clinical record is available at the point of review to help the practitioner deal safely …
WhatsApp is part of healthcare: how can it be used safely and reliably? Read More »
Burden and prevalence, life-course impact, research and investment priorities Many people say women’s health is underfunded. This is often framed in moral or political terms linked to patriarchy, historical exclusion or bias within medicine. These forces are real and well documented. But if the goal is to understand how health priorities are actually set, they …
