Top all-time · #1843
Lauren Oakden-Rayner
Personal blog · lukeoakdenrayner.wordpress.comaihealth
Lauren Oakden-Rayner's personal blog at lukeoakdenrayner.wordpress.com covers ai and health. Since 2016, 40 different Hacker News readers have linked it 51 times, most often “.98 AUC classifying race from chest x-rays (external validation)”. The last post was in 2022, but the archive is still widely read.
Too few sampled comments (12) to say how often HN recommends it.?
Why HN links it
HN readers link this radiologist and deep learning researcher's blog for a skeptical, grounded view of machine learning in medicine, covering AI diagnostic claims and the hype around them.
- Recommended for · 6 comments
- Called a pretty good overview of ML in medicine hype and its nuances, a high-quality series, and a well-needed skeptical perspective from a radiologist.
Summarised by Claude from a sample of 12 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Medical AI Researcher / Radiologist
Most-linked posts?
- .98 AUC classifying race from chest x-rays (external validation)9 people · 9 mentions · first linked 2021-08-03
- Do machines actually beat doctors? (2016)5 people · 5 mentions · first linked 2016-12-14
- Producing simple text descriptions for AI interpretability in radiology4 people · 4 mentions · first linked 2018-06-06
- The Bleeding Edge of Medical AI Research3 people · 3 mentions · first linked 2017-05-24
- Exploring the ChestXray14 dataset: problems3 people · 3 mentions · first linked 2017-12-18
- CT scanning is just awful for diagnosing Covid-193 people · 3 mentions · first linked 2020-03-23
- Do machines actually beat doctors? (2017)2 people · 2 mentions · first linked 2018-03-28
- /2017/05/03/the-end-of-human-doctors-understanding-automation/2 people · 2 mentions · first linked 2017-05-27
- The End of Human Doctors – Understanding Medicine2 people · 2 mentions · first linked 2017-04-24
- Predicting Medical AI in 20172 people · 2 mentions · first linked 2017-01-03
What Hacker News says?
That's not really the hard or useful part part. According to a radiologist and machine learning researcher[1]: "It turns out that deep learning is a very good match for some of the most time consuming (and therefore costly) parts of medicine: the perceptual tasks. We also saw that many decisions simply fall out of the perceptual process; once you have identified what you are seeing or hearing, there is no more “thin…
Comment linking /2017/05/03/the-end-of-human-doctors-understanding-automation/
on ““AI promised to revolutionize radiology but so far its failing””Submitted AI competitions don’t produce useful models as a story · 199 points
HN discussionI found the Statistical Learning self paced course on Stanford's site to be a great formal intro to ML algorithms implemented in R, and it is taught by the inimitable Hastie and Tibshirani: http://statlearning.class.stanford.edu This post on ML in medicine is a pretty good overview of everything that has been going on recently and the nuances often lost in the current hype: https://lukeoakdenrayner.wordpress.com/201…
Comment linking /2016/11/27/do-computers-already-outperform-doctors/
on “Apple Watch can detect arrhythmia with 97% accuracy, study says”Submitted Predicting Medical AI in 2017 as a story · 77 points
HN discussionI appreciate this radiologist and current ML PhD student's perspective, as a trainee myself: https://lukeoakdenrayner.wordpress.com/2017/04/20/the-end-of...
Comment linking /2017/04/20/the-end-of-human-doctors-introduction/
on “AI in drug discovery is overhyped: examples from AstraZeneca, Harvard, Stanford”Submitted The End of Human Doctors – The Bleeding Edge of Medical AI Research (Part 3) as a story · 22 points
HN discussionEveryone swooning with optimism over this result should the machine learning reddit comments on it first. https://old.reddit.com/r/MachineLearning/comments/ehpllt/dee... And also linked blog[edit]: https://lukeoakdenrayner.wordpress.com/2017/12/06/do-machine... TL;DR; There are sooo many subtlties to stuff like this that this things really shouldn't be taken at face value. This is far from replacing doctors in anyth…
Comment linking /2017/12/06/do-machines-actually-beat-doctors-roc-curves-and-performance-metrics/
on “Breast cancer detection in mammography using deep learning approach”Submitted .98 AUC classifying race from chest x-rays (external validation) as a story · 17 points
HN discussionI recommend reading "Do machines actually beat doctors?" by Dr. Luke Oakden-Rayner, who is both a radiology doctor and deep learning researcher. https://lukeoakdenrayner.wordpress.com/2016/11/27/do-compute...
Comment linking /2016/11/27/do-computers-already-outperform-doctors/
on “A.I. vs. M.D.”Submitted AI has the worst superpower medical racism as a story · 16 points
HN discussionIt might be helpful for folks to look at the blog post written by one of the authors: https://lukeoakdenrayner.wordpress.com/2021/08/02/ai-has-the... or the paper itself https://arxiv.org/pdf/2107.10356.pdf I see a lot of "oh it's probably just picking up on x y z" when x, y, and z are things they explicitly checked for: 1) "It's probably just the names or other metadata" – they only gave it pixel data to train on.…
Comment linking /2021/08/02/ai-has-the-worst-superpower-medical-racism/
on “AI Recognises Race in Medical Images”Submitted Producing simple text descriptions for AI interpretability in radiology as a story · 15 points
HN discussionIt's not really a doctor shortage, more like a service shortage: https://www.nytimes.com/2016/11/08/upshot/a-doctor-shortage-... Generally, there's an ongoing reformation of the system. From the perspective of medical insurance, the current medical system is actually too lax, in that it certifies and retains doctors who get frequent malpractice suits. http://digitalcommons.law.umaryland.edu/cgi/viewcontent.cgi?... h…
Comment linking /2017/05/03/the-end-of-human-doctors-understanding-automation/
on “When doctors can't afford to feel”Submitted The End of Human Doctors – Understanding Medicine as a story · 6 points
HN discussionHi, I'm the author of the blogpost (didn't expect to see it here!) and I largely agree with you. I think I would say that the use of private datasets isn't actually a problem though, the problem is that the methods and analysis in many of the papers is horribly flawed. I could reasonably trust a paper with good methodology - all of medical research is on private data essentially. But the majority is, as you say, pur…
Comment linking /2016/11/27/do-computers-already-outperform-doctors/
on “Predicting Medical AI in 2017”Submitted The medical AI floodgates open, at a cost of $1000 per patient as a story · 5 points
HN discussionSee this blog post from a radiologist and ML researcher: https://lukeoakdenrayner.wordpress.com/2020/03/23/ct-scannin...
Comment linking /2020/03/23/ct-scanning-is-just-awful-for-diagnosing-covid-19/
on “Hospitals Deploy AI Tools to Detect Covid-19 on Chest Scans”Submitted AI has the worst superpower medical racism as a story · 4 points
HN discussionI think there is hope, there is a very nice paper where they automaticaly produce both heatmaps and textual explanations of the label given by the neural network (used to detect and classify fractures). It is detailled here : https://lukeoakdenrayner.wordpress.com/2018/06/05/explain-yo...
Comment linking /2018/06/05/explain-yourself-machine-producing-simple-text-descriptions-for-ai-interpretability/
on “Is Artificial Intelligence Permanently Inscrutable? (2016)”Submitted The Philosophical Argument for Using ROC Curve as a story · 4 points
HN discussionFor another perspective on applying machine learning to medical imaging, I recommend the blog of Luke Oakden-Rayner[1]. He's a radiologist first, so he's in a great position to bring some well-needed skepticism to the conversation. I learned about a lot of complications that I never would have imagined as a lay-person. [1] https://lukeoakdenrayner.wordpress.com/
Comment linking /
on “How to Choose a Neutral Net Architecture for Medical Image Segmentation”Submitted Exploring the ChestXray14 dataset: problems as a story · 4 points
HN discussionA high-quality blog series by Luke Oakden-Rayner, a radiologist (MD) who is doing a PhD focusing on applying machine learning to medical images and text. The End of Human Doctors: https://lukeoakdenrayner.wordpress.com/2017/04/20/the-end-of...
Comment linking /2017/04/20/the-end-of-human-doctors-introduction/
on “Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning”Submitted The Bleeding Edge of Medical AI Research as a story · 4 points
HN discussionSubmitted AI has the worst superpower medical racism as a story · 3 points
HN discussionSubmitted AI has the worst superpower: medical racism as a story · 3 points
HN discussionSubmitted CT scanning is just awful for diagnosing Covid-19 as a story · 3 points
HN discussionSubmitted Medical AI Safety: Doing It Wrong as a story · 3 points
HN discussionSubmitted Producing simple text descriptions for AI interpretability of X-ray images as a story · 3 points
HN discussionSubmitted Exploring the ChestXray14 dataset: problems as a story · 3 points
HN discussion
