Revolutionizing Healthcare: Glass Health's AI Diagnostic Tool

0:00Back in 2021, the healthcare tech landscape saw a very interesting new company, and that's Glasshealth health that I mentioned in the intro to this. So founded by Derek Paul, who's a former medical student at UC San Francisco, and also Graham Ramsey, who is an engineer at Women's Health Company, Modern Fertility, the company initially launched as a notebook for clinicians. So the notebook aimed to help medical professionals store, organize, and share their approaches for diagnosing and treating various conditions. So Ramsey articulated that the original goal was to create a, quote, personal knowledge management system for doctors serving as an evergreen resource throughout their career.

0:37Now, this is really interesting because you see a lot of the companies that are really succeeding right now in AI are companies with data. And it's really interesting because this is a company, right? From the beginning, they were collecting data. They're allowing doctors to store a lot of their, you know, quote unquote, it's like doctors were able to dump all of the everything that they knew onto a page. And this is where they're gathering a ton of data. So this is what Ramsey said, quote, during the pandemic, we witnessed the overwhelming burdens of our healthcare system and the worsening crisis of healthcare provider burnout.

1:11That was actually Paul that said that and said, our empathy for frontline providers catalyzed us to create a company committed to fully leveraging technology to improve the practice of medicine. So back in 2001, they, you know, got this whole thing kicked off. And then in 2023, Glass Health took a pretty big pivot. So leveraging the upward trajectory of generative AI, the company shifted its focus. Now the platform is powered by a large language model that can assist in generating diagnoses and treatment options for clinicians. So physicians can input descriptions like patient demographics and symptoms and Glass Health's AI offers a likely prognosis and clinical plan.

1:53This is really interesting. And also I think this is important to talk about because this is what we're seeing. like this is this trend is all over tech right now where essentially you had this company founded back in 2021 probably raised money at a at a very high valuation um maybe they weren't seeing the product market fit they were wanting or maybe they just saw some you know new opportunities in ai and and kind of did a big huge pivot and now it's like oh yeah we're just like a an ai company to help you know diagnose things for doctors like duh that's just what our company is but i you know Obviously, it's not what it started as.

2:27And I think this is a no-brainer. Any startup that I was really actively involved in as the beginning of the year came around and we saw this big, huge wave of AI, yeah, immediately all of them turned into AI companies. We just integrated AI into everything we're doing and completely changed our product. So, you know, I'm not calling the kettle black and I actually think it's great because there's a whole bunch of, here's the thing. For a company to go from zero to hero or zero to a hundred, right? Like completely fresh and then come up with a revolutionary idea takes a lot of time. It takes energy to get investors or to get the team put together to actually build the product.

3:03and if a company is already like let's say they have some version of product market fit they have users they have a database they have some sort of user base and then they're able to add in ai features like one of my one of my companies i had when ai started hitting the forefront it was two weeks before we had some like major ai products and that's just because we already had all the infrastructure the logins the sign-ins the client base like we had everything built out and then immediately we're able just to start building these ai features and adding them on top of what we already had. And it felt like a very robust system.

3:35Now, if we had thought of the idea for what we had rate, like when AI, when ChinaGPT came out, we'd probably still be under development working on building, you know, what is now, what was, you know, we were able to get done in two months. So I think this is awesome. I think this is something we're going to see in the future. This is definitely a trend and, you know, good on Glass Health for kind of seeing this and grabbing this traction. So I think while AI's promise in healthcare is quite, you know, it looks very attractive. It's not without some of its caveats. So Babylon Health, which is an AI startup backed by UK's NHS, has faced a lot of criticism for essentially making inflated claims about its capabilities.

4:13So Glass Health's offering might also bring about, you know, some ethical concerns. Of course, there's, you know, people talk about data biases, as the AI's trade on health records that could be influenced by different, you know, racial, gender, socioeconomic biases. but you know it's like I guess you kind of have to ask yourself even like geographically right like the AI might be trained on the United States and maybe the diet of the United States is completely different than the diet in let's say a country like Argentina or Ethiopia or France right like there's all sorts of different factors and if you know an AI is specifically trained just on one area maybe it's going to miss some things that are relevant to people in other places so there's all sorts of like things to look at in that regard but in any case addressing a lot of these challenges paul emphasized saying quote glass connects llms with clinical guidelines that are created and peer-reviewed by our academic physician team our physician team members are from major academic medical centers around the country and work part-time for glass health we ask our clinician users to supervise all of our llm applications outputs closely treating it like an assistant that offers helpful recommendations.

5:26Here's one other thing I did want to bring up on this whole like, you know, like, like people essentially are kind of poking holes in what these models are not able to do. And I think sure, like, it's totally fair. If you know, like make sure if a model saying it can do something and it isn't like you're holding them accountable to being like truthful, whatever, I get that. But the people that just want to criticized for criticism's sake, I will say to those people, like right now, of course, even like my thing of like, oh, you're living in a different geographic area, and maybe the model was just trained on Americans, and there's like differences between people that live in other places.

6:02So here's the thing, current medicine and current medical journals, which is where a lot of doctors get their information, may just very well have the exact same problem. So it's just all about the data. And what I think is interesting is it's probably actually AI models that could help solve this problem in the future. You can imagine an AI model like this that diagnoses diseases, but it asks you exactly where you're from. It looks at all the latest data from that specific area, studies in your specific geographic location, specifically for your body type, your ethnicity, your background, everything.

6:34I've heard a lot of talk about people saying like, oh yeah, like my ancestors used to eat potatoes and your ancestors used to eat rice and yada yada. So today, like my body can digest this or that better. And there's all sorts of interesting things like that. And I mean, I am definitely not a nutrition coach. I'm definitely not a medical expert with medical advice or anything. And so, I mean, I can't tell you exactly how accurate that is, but I've heard things like that in a lot of different areas. And what I can say is our current approach of medicine and everything else, we definitely are just treating everyone like the exact same like, oh, you have x, y, and z, okay, here's the pill for x, y, and z, where it might not actually work as well on you for your type of, you know, body or whatever.

7:21So I think the cool thing about a lot of this AI is I think it does have the possibility of becoming more customized, more personalized to you. And I know right now, people might be like, yeah, right, like, look at Chet Gpt, it's got all sorts of errors and problems. It's like, give this give this tech, like five years, 10 years. If we don't figure out any way to make it better other than to make it more personalized, I think we're going to see some really incredible advancements. And it's going to be a lot more effective at, you know, doing whatever it needs to do, just based off of like, let's say you train an AI specifically for you, everything about you.

7:52It's got your like, you know, your genealogy in there, like whatever, I don't know, right. But it can really dial in on what it thinks can help you best. And so yeah, I think it may not be there right now. But that's definitely where this stuff will go in the future. It's going to seem like, you know, a no brainer in the future that we you know, it's going to seem crazy that at one point, the entire world used one giant model called chat GPT, and everyone had like the same thing with the same data set, whatever. So I think it'll be interesting to see how that evolves. I think despite all of these complex complexities, Glass Health has already secured a significant market validation.

8:26So they They just did a$1.5 million pre-seed round led by Breyer Capital back in 2022. And this was followed by acceptance into Y Combinator's winter 2023 batch. I think this certainly adds weight to their venture. And also, I think with more than 59 ,000 users and a direct-to-clinician monthly subscription offering, Glass Health is positioned for growth. I think the company plans to launch an electronic health record integration enterprise, which is essentially offering with HIPAA compliance and already has 15 health systems on the wait list. So Paul also commented on this and said, quote, Glass is different from LLM applications like ChatGPT that rely solely on their pre-training to produce outputs and can more easily produce medical information that is inaccurate or out of date.

9:14and so I think while you know Glass Health navigates the choppy waters of this whole healthcare innovation and ethical AI use it also continues to resonate with both investors and the medical community with a total of 6.5 million dollars in funding and four years of runway I think it's worth keeping an eye on how this kind of ambitious startup is you know gonna potentially be redefining the role of technology in healthcare in the future so definitely one we'll continue to follow below.