Last post I introduced the big question - "Are doctors going to be replaced by computers soon?" We also saw one possible answer: "Yes", which we are going to investigate in this series of articles. Over the next few posts we will start building a foundation for answering this question, by defining and exploring some of the … Continue reading The End of Human Doctors – Understanding Medicine
I have emerged, blinking, from the darkness of grant/paper writing purgatory (a.k.a December to March in Australia). It is time to get the blog going again, and to make up for the long gap in posts I'm going to start with the big one. The question I get every time I tell a colleague what I … Continue reading The End of Human Doctors – Introduction
I love massive open online courses. I love everything about them. I love the format. I love the platforms. I love the teachers. I love the flexibility and the lack of friction. And I love dropping out of them. This picture turned up in my Twitter feed recently, from Class Central by way of the … Continue reading Why I just love dropping out of MOOCs
Welcome to 2017! What a blast 2016 was. It seemed like every day there was a new, massive breakthrough in deep learning research. It was also the year that the wider world really started to take notice. The media, professional groups, and the general public all climbed aboard the AI hype train in 2016. Governments commissioned … Continue reading Predicting Medical AI in 2017
In a recent blogpost I explored how to critically read medical artificial intelligence research, focusing on the relevance of these experiments to clinical practice. It has since struck me that we don't have a simple, clear way to discuss the idea that some studies are still a still a long way off use in the clinics, and others … Continue reading The three phases of medical AI trials
After an amazingly high number of readers for my last blog post (thanks to everyone who read and shared it), I have starting writing a series of posts on the big question in radiology – will radiologists be replaced by machines in the near future? Geoff Hinton thinks we have five to ten years left, and as one … Continue reading Standardised reports might be good for humans, but they are probably bad for artificial intelligence
If you ask academic machine learning experts about the things that annoy them, high up the list is going to be overblown headlines about how machines are beating humans at some task where that is completely untrue. This is partially because reality is already so damn amazing there is no need for hyperbole. AlphaGo beat … Continue reading Do machines actually beat doctors?
Thanks again to HISA for inviting us, and for the excellent Q & A / meet and greet after the talks. In particular thanks to Chris Radbone for organising the event. We got a tour of SAHMRI before we started, and I can say that the building was as impressive from the inside as is from outside. … Continue reading Health Informatics, big data and computer gamers @ SAHMRI
I will be giving a talk about my PhD project to the Health Informatics Society of Australia (SA branch) with my supervisors Professor Lyle Palmer and Associate Professor Gustavo Carneiro. Professor Palmer works at the School of Public Health at the University of Adelaide. He is a world-renowned genetic epidemiologist and a previous executive scientific director … Continue reading Seminar @ SAHMRI
Last month I presented a talk on my PhD project at the 2016 Aus and NZ College of Radiology and Radiation Oncology annual meeting, which is the first time I have talked about it publicly. We have not published any major papers yet (our first big one is just about ready for submission), so there hasn't been … Continue reading Precision radiology, deep learning, artificial intelligence, oh my!