AI Quality Control Records from the Front Lines of Healthcare

In 2036, AI assistance for primary healthcare had already been rolled out everywhere. Yet the cloud-based large model at Linjiang County Hospital read an early-stage lung cancer case as showing no abnormalities in either lung.

Lin Mo, a veteran who had started out taking jobs in an urban village and spent over a decade specializing in medical AI, was invited back by the old hospital director to rescue the model. The big tech company's model scored as high as 98% in benchmark tests, but in actual use it was hampered by old CT scanners and bandwidth limits, and drifted badly between hospitals. He brought out the LM?Clinic engine, sealed away for years. With just a few hundred anonymized scans from the hospital and a domestically made edge device, it could produce interpretable diagnostic recommendations, reduce false negatives, and roll back to a hardware-compatible version.

From county-level imaging centers to regional trusted data spaces, from model drift to adapting domestic computing power, he held fast to one principle: AI can only assist. It must never replace a doctor's signature.

This novel and its characters are entirely fictional. Any resemblance to real people or events is purely coincidental. Do not imitate.