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Getting image recognition to work to "replace" radiologists is both a game-changer and a HUGE money-saver and thus a GIGANTIC opportunity. Radiology is the mos

Getting image recognition to work to "replace" radiologists is both a game-changer and a HUGE money-saver and thus a GIGANTIC opportunity. Radiology is the most common specialty and one of the highest-paid in just the US -- 40,000+ radiologists earning $350k/year (so maybe $15 bn in salaries). Radiologists and thus some of the smartest & most capable people in the country and they spend the whole day just looking at images...computers should be doing this!! Not only that, computers will soon better...for many skin tumors and others, even the leading human experts differ in their opinion, so humans today out-perform computers but I don't foresee that being the case for long. A game-changer in cancer treatment would be "early detection". Once it gets to be inexpensive to analyze images, then we can have vastly earlier cancer detection...you could work into a scanning machine in a local pharmacy, get scanned & get the analysis right there...you could go in for monthly scans. Theranos had something of that vision with a drop of blood in pharmacies which could also provide very early detection of cancer...but they didn't execute technically among other issues.

mikekij 9y ago
I've been looking at this space for a few years. I've come to the conclusion that one of the biggest obstacles to ML replacing/supplementing radiologists is the malpractice ambiguity. If a doctor misses a lesion on a chest Xray, the lawyers know who to sue. What if a ML algorithm that no human understands misses this. Who is liable? It's another sad example of technological progress in healthcare being stifled by bureaucracy / liability concerns.
- avvakum 9y ago
  Liability is of a radiologist is ultimately offset by malpractice insurance. Similarly, the lawyers would go for ML algorithm developers. Now I can see ML insurance business with premiums tied to ML clinical performance ... Obviously there has to be a legislation in place for this.
- wst_ 9y ago
  How is that possible? Are these images so obvious as 2+2=4? Legitimate question, I am layman in this area.

mikekij 9y ago

I've been looking at this space for a few years. I've come to the conclusion that one of the biggest obstacles to ML replacing/supplementing radiologists is the malpractice ambiguity. If a doctor misses a lesion on a chest Xray, the lawyers know who to sue. What if a ML algorithm that no human understands misses this. Who is liable? It's another sad example of technological progress in healthcare being stifled by bureaucracy / liability concerns.

avvakum 9y ago
Liability is of a radiologist is ultimately offset by malpractice insurance. Similarly, the lawyers would go for ML algorithm developers. Now I can see ML insurance business with premiums tied to ML clinical performance ... Obviously there has to be a legislation in place for this.
wst_ 9y ago
How is that possible? Are these images so obvious as 2+2=4? Legitimate question, I am layman in this area.