A working notebook from a neonatologist at the Wilhelmina Children's Hospital, UMC Utrecht. Read what I'm building, why I'm skeptical of half of it, and where the field is actually going.
In late October 2026 I'll stand on a stage in Lyon for twenty minutes and talk about big data, AI, and sepsis prediction in the NICU. I've been quietly uneasy about it ever since. Not about the speaking part — about what I'm supposed to say.
Read on Substack →A live PubMed search for late-onset sepsis prediction models, with Claude as the research partner. Seven academic groups, two systematic reviews, every query archived. The full evidence base for the series begins here.
Read on Substack →Four late-onset sepsis models, read side by side. The headline AUCs land in a tight band — but each one answers a different question. Similar, but not the same. The full eight-dimension comparison lives on the companion page.
Read on Substack →The same two decisions, turned onto my own paper. The detection fraction went in the abstract; the 4% precision stayed in Table 3. A self-critique of Berg 2023, read against its own supplement — the working file is on the companion page.
Read on Substack →I'm Daniel Vijlbrief, a neonatologist and clinical researcher at the Wilhelmina Children's Hospital, UMC Utrecht. I work on AI implementation in neonatal care — clinical decision support, sepsis prediction, and the unglamorous question of whether any of this actually changes what we do at the bedside.
Lately I've also been working with large language models in clinical workflow — including an AI-generated discharge letter now in routine use on our department, and the experiment you're reading now.
This site is where I think out loud.