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Inexpensive x-ray hardware

Hacker News

Inexpensive x-ray hardware

Hi HackerNews! I'm Adam, a young lad who has been working with some friends on democratizing x-ray imaging, through lowering the cost of such hardware to a point where it's affordable. (from $80,000+ to $3,000 or less). A short summary of our project is here: http://aperture.systems/mission.pdf And, a big folder of cool x-ray pictures, gifs, and things we have built is here: https://drive.google.com/open?id=0BwIWrZZX8IW6fjR4LUVOMjExSHN5M0VGQm5jbUtNVTNuNDJqbE1Ja21lckprM3FlV2NEekk At this point, we're bootstrapping our work by repairing x-ray sensors for people. We'll be applying to YC this year, and are looking for angels who'd like to help us ship desktop CT scanners to workshops all across the country (as our first product). I'm sharing this on HN to see what y'all think of our project, and, to find people excited to help make it a reality. Cheers! -Adam

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% 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: google, new, open · Missing: mac, agents, macos
64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, 000, io · Missing: https docs, just released, exist
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: google, scanner · Missing: mobile apps, ios, personal
52%52% 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
36%36% 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
18%18% 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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