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184 points yeatsy | 1 comments | | HN request time: 0s | source

Hi HN,

I’m Joshua, a student, and I’m excited (and a little nervous) to share something deeply personal that I’ve been working on: Islet, my diabetes management app powered by GPT-4o-mini. It’s now on the App Store, but I want to be upfront—it’s still very much in its early stages, with a lot more to go.

I was diagnosed with Type 1 diabetes while rowing competitively, and that moment changed everything. It wasn’t just the practical challenges of managing insulin, carb counts, and blood sugars; it fundamentally shifted how I see myself and the world. It forced me to slow down, prioritise my health, and take control in ways I never had to before. My outlook on life became more focused on resilience, adaptability, and finding solutions to problems that truly matter.

This app started as a pet project over the summer, a way to see what I could create using ChatGPT and explore the potential of LLMs to help with real-world challenges. At first, it was just about making my own diabetes management easier—understanding patterns in blood sugars, planning meals, and adjusting routines. But as I worked on it, I realised it could do more.

Right now, Islet offers personalised meal suggestions, tracks activity, and provides basic insights based on the data you enter. It’s far from complete. Even so, the process of building Islet has already taught me so much about how powerful AI can be in creating personal, meaningful tools.

This project is deeply tied to how my diagnosis changed me. It’s about more than managing diabetes, it’s about showing how anyone, even a student experimenting over the summer, can use AI to potentially solve real, personal problems. I believe tools like LLMs have the power to democratise solutions for all, making life just a bit easier for all of us.

If you’re curious, you can check it out here: https://apps.apple.com/gb/app/islet-diabetes/id6453168642. I’d love to hear your thoughts what works, what doesn’t, and what features you think would make it better. Your input could help shape the next steps for Islet.

Thanks for reading !

joshua

Show context
Nk26 ◴[] No.42168772[source]
Does the photo recognition attempt to carb count what it sees? Is that even possible? My son is a T1D and he still struggles with carb counting.
replies(3): >>42168783 #>>42168850 #>>42171898 #
jrflowers ◴[] No.42168850[source]
It is absolutely not possible to carb-count through photo recognition in a way that is reliable enough for a diabetic to safely use to make treatment decisions.
replies(3): >>42169120 #>>42170332 #>>42171885 #
Nk26 ◴[] No.42169120[source]
I meant more in a general way, like a piece of pizza is usually around X carbs. We have apps that make the guess a bit easier but it's almost always a guess. I was thinking could this look at a photo and know there's a sweet potato, a piece of chicken and some corn and give a basic idea.
replies(2): >>42169207 #>>42169211 #
jrflowers ◴[] No.42169207[source]
The answer is still Absolutely Not, especially since all food can involve a treatment decision for people with type 1 diabetes.

Pizza is a good example of why not. Slices come in very different sizes, sauces have very different carb content, so do crusts, and toppings.

Edit: for example this pizza(1) is 31g per slice and this pizza(2) is 73g per slice. The difference is very meaningful and the “general idea” given by photo recognition would likely be wrong to the point of dangerous for a diabetic in both cases.

If you’re looking for software that can make a guess simply for the sake of generating a number to write down and not be used in any way, a random number generator would be safer since the risk of output being misconstrued as actual information is much lower.

1 https://www.costcobusinessdelivery.com/kirkland-signature-ca...

2 https://sbarro.is/product/bbq/

replies(2): >>42169301 #>>42170027 #
pimeys ◴[] No.42170027[source]
Yep. And the issue with pizza is the amount of fat that comes with the carbs. This quite often (depending on the position of the moon) gives you some of the carbs when you eat it to your blood, and the rest will come after several hours. What you want to do is to inject a bit of insulin before eating, then after two or three hours more while measuring your glucose levels.

Of course if you eat a Neapolitan pizza with not that much of cheese everything changes again. And YMMV, I'm just talking about my experiences.

replies(1): >>42170316 #
1. je42 ◴[] No.42170316[source]
Not only fat plays a role with pizza, but also the amount of protein in it. When having pizza we usually add protein to the carbs. 50% immediately bolus. Other 50% spread over 3-4 hours, and let AAPS dose the insulin.