[neurobashing]

I'm sure it's an interesting technical challenge with huge amounts of complex, nuanced debate involved, and it could have a huge impact on health care.

That said, my wife is an oncology nurse, and I will bet everything that no machine will ever get better at predicting than an experienced, skilled nurse. Humans are built to read humans.

[mcny]

» my wife is an oncology nurse

Have you ever asked her if she wants to do the job of predicting when a patient will die? How many hours would she need to spend reading the patient's history to come up with a prediction she feels satisfied to use to decide what service the patient will get? I'm not a medical professional but my gut reaction is I don't want to do anything with predicting or sentencing if some machine can do it almost as well as I can.

I remember this story of a radiologist who told me he thinks we spend too much money for too little during the last about six months of a patient's life. If we had better information on when the last six months starts, maybe we could reduce the cost of healthcare? Apparently, we spend cost to 18% of GDP on healthcare in the US? Iirc, most of Europe is closer to 12?

[evandijk70]

I would be very willing to take that bet on a 30 year horizon

Just think about the machines/algorithms your wife already (indirectly) uses to predict outcome for patients.

- An MRI scan, which is created from physical laws (Maxwell's law together with a quantum mechanical understanding of hydrogen atoms) and reconstructs a 3D-image of the different tumors. Knowing if and where metastasis are present have an enormous impact on the prognosis.

- The algorithms used to align sequencing reads from biopsies to determine the mutation status, which are critical to determine the prognosis of some tumors.

In fact, I'd wager that if your wife did not have access to these algorithms, she would already perform worse. And, in my opinion, the distinction between machine learning and the algorithms used to reconstruct 3D-images or align sequences is somewhat arbitrary.

[adrianN]

"ever" is a pretty long time though.