A.I. vs. M.D.

So here is the warning: Medical startups are hard, really hard. - It is difficult to apply research on 32x32 cat icons on 15megapixel xrays. - It is difficult to get data without year-long contract efforts - It is very difficult/expensive, if not impossible, to use cloud resources due to HIPAA and localization rules so you need to build your own on-premise GPU grids like we did - It is difficult doing most medical things in the USA unless you are on the revenue side (e.g., collections, increasing yield, etc.) -- we got so many raw deal partnership offers in the US that we went overseas to trail our product.

The entire medical system in the US is corrupt from the ground up, geared to maximize revenue with minimal lawsuit risk. Patient care rarely enters the conversation internally. I thought financial services was bad (my past career), but at least the metrics were all agreed upon by everyone. In medicine, everyone has an agenda, often diametrically opposed to other parties.

Most of the automation in a modern airliner, for example, isn't there to make the plane "fly itself" from point A to point B -- it's there to do things machines are good at in order to reduce the workload of the human crew, so they have more time/energy to focus on the things humans are good at.

Flight plans, for example, are still decided on by humans, even if a programmed computer carries out many aspects of the plan once decided upon. Same for en-route deviation from the prior plan in order to either avoid bad weather or reach good weather (where "weather" is kind of a broad term, and includes things like winds which would help/hinder an airliner). Although "autoland" is a feature, it's not something that's used every time and can be moderately complex to set up, since a bunch of factors have to be decided/input by a human. And of course the final decision to land or go around is made by a human.

Which drives home the fact that automation, in aviation, is a partnership between humans and machines, with humans benefiting and being more productive from offloading some work.

A lot of fields should be looking at that as a model.

Let's be honest here Machine-Learning is perfect for medical diagnosis.

X-Ray or any visual, the video to text translation is 99% perfect now, no way a doctor can be trained to beat the system's, given humans can only deal with what '7' issues at once.

I think really SURGERY is where it will go, machine's (ROBOTS) will make the machines much like 3d printing now. The new machines will be surgeons to handle any surgery and never make a mistake.

The real issue here is 'politics', in the USA/EUROPE it will be dead, because of the lawsuit legal moral hazard business, in ASIA however you will find diagnostic medical computers just a tablet for less than $100, show it a photo/video, and it will diagnose, and the best the AMA/big-pharma will do is BAN this stuff on USA soil.

Same with surgery robots the vested USA interests will bitch &moan, in the meantime china/japan will crank out perfect robot-surgeons.

Hardly anything that a machine can't do better than a human in this area.

The USA has the worse medical care in the world for the highest price, the rest of the world has no choice, in order for India/Mexico/Thailand to continue to provide a hospital visit & pharma for a few bucks, they must embrace this TECH, and they will. On the other hand the USA will continue to try and collect $100K/day from a sick person, and lobby all they can to kill high-tech in the USA.

I think it was predicted long ago, but in the USA people will die because they can't afford to see a doctor or get medicine, 90% of the world doesn't have an AMA, and let's anybody who wants to can pass the test become a doctor and get into med-school.

Nobody in ASIA will stop a smart young kid from developing a robot surgery system, and or human diagnostic laptop. All hardware is around $10, and 3d printing machines are super cheap, all can be had from aliexpress.com for a few bucks.