Not clinical decision support.

Human progress in clinical medicine is stunted by the speed of evidence generation. Randomised trials guard against mistaking association for treatment benefit, but they are slow, expensive and cover only a fraction of clinical decisions. A 2013 Oxford hospital audit found trial evidence supporting about one in five primary treatments; many others had convincing non-experimental support1. One UK exercise estimated £770,000 for specialist trial support2; a 2018 analysis estimated a median US$19m for trials supporting new drug approvals3.

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The Fantasy of Technology from Ursula Franklin’s 1989 lectures. Nothing new under the sun.

cafe shadows in kentish town

Simpson's Paradox

Via Björn N. Persson

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Happy (belated) Birthday Pandoc! This might be the first command line tool that I ever used. Couldn’t have written my PhD thesis without it. Super cool, and still going strong.

Prefer compositions to features in ML-Ops

I had an interesting conversation with a colleague this week. He has built a model that predicts physiological stability for inpatients on intravenous antibiotics using a recent history of vital signs. The purpose is to identify patients who could be switched to oral antibiotics and therefore discharged sooner. I had also considered that the underlying physiological stability, or its inverse, was a common component of many acute hospital prediction problems. But I wonder if we could take this further when considering how we build features under the ML-Ops paradigm.

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James Wilson …

We are entering an era where someone might use a large language model to generate a document out of a bulleted list, and send it to a person who will use a large language model to condense that document into a bulleted list. Can anyone seriously argue that this is an improvement?

via Ted Chang in The New Yorker

Training may want the large data center, but we’ve long since hit the point of diminishing returns. There is effectively no more text to train on, as even the LLM systems of a few years ago were trained on almost all the coherent text in existence

via Pivot to AI

So good. One Battle After Another 🍿

Finished reading: Pereira Maintains by Antonio Tabucchi 📚

Boring machine learning is where it’s at

go grab a spreadsheet and figure out how to get the best result on a boring economics problem with a boring algorithm; Don’t worry so much about making a painting or movie with GANs, we’re already really good at doing that and enjoy doing it.

Store git credentials for a day from the command line. As of Aug, 2021, a ‘personal access token’ must replace your password.

git config --global credential.helper "cache --timeout=86400"

via https://stackoverflow.com/a/5343146/992999

Python decorators

I finally understand Python decorators!

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Link list of programming tips

Link list of programming tips A crowd-sourced list of recommendations for learning good programming style from the lab group. Software Design in Python Pragmatic Programmer Clean Code Philosophy of Software Design Code Craft The Missing README Beyond the Basic Stuff Refactoring code All the little things Nothing is something

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iA Writer to micro.blog

I just discovered that iA Writer publishes to micro.blog. How cool! Am going to see if I can use this to improve my writing habits as per Andrew Gelman's recent comment: Eventually everything makes its way from conversation to blog to publication. A great philosophy.

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Far from being an aberration, Dominic Raab might be the right man for the job – an out-of-office foreign secretary for an out-of-office country.

Via Marina Hyde