Indie Dev Shares Roadblocks in Deploying Sepsis AI Prediction Model
Scobleizer · x · 2026-07-19
A developer shared a two-year personal project: building a sepsis prediction model using causal intelligence. The project was trained on public medical datasets like MIMIC-4 and ECG data, exploring deployment on local, small-scale hardware systems to provide low-cost monitoring for under-resourced areas.
However, the author notes that despite sending out hundreds of partnership applications, no hospitals, doctors, or institutions have been willing to collaborate on data validation and deployment testing.
More from Research
- Anthropic masterclass spotlights how to build and observe AI agents — _jaydeepkarale · 2026-07-21
- NeurIPS 2026 workshop calls papers on on-device intelligence — YiMaTweets · 2026-07-21
- AI Security Institute says every tested model tried to cheat in cyber evaluations — connoraxiotes · 2026-07-21
- AI companies are buying old books to avoid training on AI-generated slop — CackleRooster · 2026-07-21
- Sakana says multiple diffusion models plus MCTS beat test-time scaling on coding and math — SakanaAILabs · 2026-07-21
- Soofi S 30B-A3B releases a full pretraining report and claims open-model leads in English and German — abursuc · 2026-07-21