3 ms·
It's my understanding it's sometimes exactly those obvious abnormalities that are missed by radiologists.
by bartimus 8y ago
It's my understanding it's sometimes exactly those obvious abnormalities that are missed by radiologists.
- nitrogen 8y agoAdding another lossy step will only make even more anomalies get missed, or worse, misdiagnosed as something else (I'm thinking about the photocopiers that sometimes change numbers in documents). The argument that "our system is already bad so we should just merge this new bad component because it doesn't make it worse" is bad in software, and unacceptable in medicine.
- tntn 8y agoI don't think that is a fair characterization of what I wrote. If the scanning process has a sensitivity of 99.999%, and the next stage in the signal chain has a sensitivity of 50%, and we consider what happens if the MRI sensitivity drops to 99.9%, that's well in the noise in terms of diagnostic value. Use some of the extra money freed up by doing the MRI 10x faster to pay a radiologist to look at the scan for 10% longer, and perhaps the net accuracy has improved. What is unacceptable about this kind of holistic reasoning about the system? High performing systems are frequently not composed of perfect components.
- nitrogen 8y agoIt's fine to talk about statistical accuracy when the distribution is somewhat normal. ML systems we've seen so far don't typically degrade in nice, statistical, predictable ways. Omitting 90% of samples (based on 10x speed claim) leaves an awful lot of room for bizarre errors.
- bartimus 8y agoOne advantage of software is that it can't really have a bad day. The radiologist can be affected by external human factors. Perhaps an angry wife and a dinner getting cold at home. He might not take the extra picture a bit further down the lower back where the golfball tumor was growing (story from my mother-in-law).