Yuji Tachikawa, a world renowned theoretical physicists, reports Claude Fable solved a problem that he and his collaborators were stuck on for the past 6 months
A bit late here, but I thought I'd mention something in addition - most hospitals and doctors don't want to take on the burden or supporting something new and specialized. They will focus on providing care and buy support. Some have small IT departments, but even IT support is regularly contracted out.
There are a lot of ongoing costs as well. Medical insurance is expensive, and there's a lot of process that is ongoing. A lot of effort goes into security, both monitoring and pushing updates. Medical device companies must also undergo regular audits of our quality systems, look up QMS/eQMS, where FDA reps will spend about 1 week a year reviewing everything we've done over the last year. Generating all the documents for those audits takes a lot of time (aka cost). That's not complete list, but this is in addition to regular SaSS costs.
Being in the medtech/AI industry (our company, Eyenuk, created the 2nd autonomous AI approved by the FDA), nothing seems too strange here.
I've seen subscriptions supported, and the pricing doesn't seem alarming. If you look at any medical bill that includes lab work, or anything medical related, this is really cheap comparatively.
The cost of everything is required to lure companies into the space. The cost of research, running a clinical trial, the FDA approval, certifications (SOC2, etc.), insurance, etc. still push many companies away. In fact, in the EU, where the cost is lower, the approval process is getting harder (MDR) and many companies are leaving the market.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
I'm genuinely curious... If the pizza box is greasy, I tear off the bottom (some boxes are perforated to make this easy even) and toss that in the green bin, which is allowed where I live. I assume anything not greasy/dirty can be recycled. Am I doing it wrong?
The thing with programming is that it either works or does not work, but there is a huge window of what can be called art.
With no training, I, or even a 1 year old, could make something and call it art. I wouldn't claim it's very good but I think most people would accept it as art. The same cannot be said for programming.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
Eyenuk, Inc. | Medical Device Software (AI) | Los Angeles | Full-Time
About the company: At Eyenuk, we develop AI-based software medical devices for the detection and monitoring of sight threatening eye disorders, such as diabetic retinopathy, macular degeneration, and glaucoma, and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first and only FDA cleared AI technology for the autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada. Eyenuk in backed by over $40M investment, including a recent $22.5M series A funding.
About the positions: We are hiring software (full-stack) engineers. We are a small, growing team and are therefore looking for people who are generalists and like to learn. Experience with Python and cloud technologies is a plus. Experience with cybersecurity and/or HealthIT is also a plus.
Eyenuk | Medical Device (AI) | Los Angeles | Full-Time | hybrid (mostly remote but occasional onsite meetings/events)
About the company: At Eyenuk, we develop AI-based software medical devices for screening, monitoring, and diagnosis of eye disorders such as diabetic retinopathy and glaucoma and systemic disorders such as cardiovascular disease and dementia. Our EyeArt AI system is the first FDA cleared AI technology for autonomous detection of both more than mild and vision-threatening diabetic retinopathy. EyeArt is also approved for sale in the EU and Canada.
About the positions: We are hiring software (full-stack) engineers and CV/ML engineers. We are still a small team, and so we are looking for people who are generalists. Experience with Python is a plus. Experience with cybersecurity or HealthIT is also a plus.
The original article title was a bit click-baity so I put something more appropriate.
I work at the company (Eyenuk) referenced in this article, and have worked with some of the article contributors. I wanted to share because it captures many of the lessons we (us at Eyenuk and our early customers/partners) have learned about the challenges of getting a medical AI product out into the real world.
FWIW, figuring out what to build is often more difficult that building a product. It would probably take much less than 6 months to rebuilt the product given the knowlege you've gained along the way. Maybe it's worth getting a new technical partner or hiring some devs and re-building the product. Perhaps you can ask your co-founder to let you use the current product and pay for support in the meantime while you find a team to build the next version.
Eyenuk (https://www.eyenuk.com) - we are healthcare and AI company, working to prevent the leading cause of blindness among working age adults (diabetic retinopathy). This not only saves people's vision, which is hugely important, but it also helps avoid the societal cost of taking care of those who have lost their vision.
- We have calls with grandparents regularly. My kids will say hi, but then they go play (usually on a screen so they are not too wild while we talk). Myself and my parents would love to have a game (and be willing to pay) where the grandparents and kids can play together on, say a TV, while having the phone/tablet run the video call.
- We had this problem with "low quality" games until we got a Nintendo Switch. Games aren't free/cheap like on phones, and so we have fewer. The kids focus more on a limited set of games and they're not full of ads.
I work an an AI company where we screen for Diabetic Retinopathy. The company is a decade old, and has validated in huge studies (over 100k patients). It's a hard problem that we have all worked very hard to solve it. At the same time, it's easy to build an AI tool that looks at an image and says healthy or unheathly (or poor quality image). So the bar is low for making something that is appears functional.
But hardly anyone makes good AI tools, so studies that look at different AIs systems see lots of the bad ones. It's always a bummer when the headlines are all dismissive of AI in general. Googling "diabetic retinopathy AI" the top result is "Artificial Intelligence Falls Short in Detecting Diabetic Eye Disease" (https://healthitanalytics.com/news/artificial-intelligence-f...), yet if you read the article it says one tool is better than humans, which to me, is the real takeaway.
I hope this goes forward. Not just for the speed, but the energy benefits.
One thing I love about C and golang is how fast they make hardware feel. They can do much more with less hardware. I love writing Python, but it does feel a bit heavy. If every machine using Python required half as much hardware/power that would be amazing.