Type 1 Diabetes Simulator

Hacker News

This simulation was designed to give a general sense of the dynamics of insulin, nutrition and blood sugar, the kinds of decisions that need to be made to manage the condition, and try to create some awareness of and empathy for the condition. The simulator recreates the metabolism of a young person, with a continuous glucose monitor and a manual (non-closed-loop) insulin pump. It models multiple factors that impact insulin sensitivity, such as hydration, exercise, stress, illness, and high blood sugar. The insulin pump can be configured like a real insulin pump, with different carb ratios, correction factor, and basal rates. You can also disable the CGM and use finger sticks only, as a kind of "hard mode". Try getting through a day or two and see how you do. Thanks for any feedback and questions.

Visit product View on Hacker NewsMar 16, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, models · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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