5 ms·
I 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
by tntn 8y ago
I 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.