What are some good ways for a programmer to help the field? Maybe learning data science would allow me to help researchers while not knowing medicine myself.
I hope this isn't bad form posting outside of the monthly Who 's Hiring post, but my company is hiring in data engineering and DevOps. My team develops machine learning classifiers for cancer diagnostics. If you (or anyone reading) are interested I'd love to hesr from you: andrew@veracyte.com
One of the main reasons medical advances are are coming out hard and fast is because of "new apps or web pages."
I really don't get this anti-tech bent. These technologies and connections are what is transforming science everywhere.
Personally I think saying most web apps are a waste is like saying the space program is a waste. Personally I think these cutting edge technologies that seems to have no use are taking us amazing places.
While I think you have a point, I think this line is taking it a step too far.
If a successful space program completely failed to actually produce any side effect innovation, at the end of the day, we still go to space.
If a successful web app fails to produce side effects, you have a web app. Depending on the app, this might be a good thing, but it's hard to reliably say that a web app is comparable to going to space.
In my mind, the advantage of having so many smart people working on trivial applications is that the risk of failure is low. If they were developing these technologies in the medical world, the risk of failure is debilitation and death. Comparatively, a giant privacy intrusion or not being able to play League of Legends for a day is something I can, literally, live with.
Unfortunately bioinformatics-in-practice tends to be about 10 years behind the rest of the tech sector, and the only thing that the giants of biotech share with their tech sector counterparts is a love for IP. Still, an inflow of ambitious tech talent into the biotech and biomedical space could hack the industry open. Then again, there's also regulatory capture.
It's a fantastic intersection of software development, pattern recognition and algorithmic development in a space that gives your work definite meaning - spending your days looking at images of people with cancer, osteoporosis, arthritis, lung disease etc can help focus you on the MVP that matters. You learn some radiology as you go too; I'm pretty good at KL scoring for OA on hip and knee radiographs for example.
Development in this space can also have it's frustrations, having to combine the latest innovations with the need to meet FDA and European regulatory requirements requires a little lateral thinking sometimes. Historically there was a reluctance in the field to adopt newer technologies but in the last 5-10 years that has really started to change with a lot of imaging moving into the cloud and the regulators waking up to fact that software isn't built like a syringe!
It might have partially been his cancer. I am convinced that he was on point nonetheless.