Evidence · Health
The diagnosis that arrives earlier
No field shows the benefit of AI more clearly than medicine. The numbers on this page are not vendor promises: they are results from published clinical studies, with tens of thousands of patients and control groups.
In search of the cure: catching the fatal earlier
In Sweden, the MASAI clinical trial followed 80,033 women through breast cancer screening. Half had their exams read the traditional way, by two radiologists. The other half had the support of a computer vision model. The AI-supported group found 20% more cancers, without increasing false positives.
And it found them with less human effort: the radiologists' screen-reading workload dropped 44%. It is the pattern that repeats across the good uses of AI in medicine. The machine did not replace the doctor; it took the repetitive volume off their hands, so attention is left where it decides. The trial's final results, published in The Lancet in 2025, confirmed what the early numbers showed: with AI support, fewer aggressive and advanced cancers slip through screening.
Figure 1
Cancers detected per 1,000 women screened
+20%
Traditional double reading, by two radiologists
AI-supported reading
20% higher detection, with the same false-positive rate and 44% less reading workload.
Source: Lång et al., The Lancet Oncology, 2023. MASAI randomized trial, 80,033 participants.
Hours worth lives
Sepsis is a runaway infection in which every hour of delayed treatment raises the risk of death. An AI early-warning system was deployed in five American hospitals and evaluated over more than 590,000 monitored patients. When a doctor confirmed the alert within three hours, in-hospital mortality among sepsis patients fell 18.7% in relative terms.
The model made no decision on its own. It read vital signs, labs and notes continuously, something no human team can do for every bed at once, and called the doctor earlier. The decision stayed human. What switched sides was time.
Figure 2
In-hospital sepsis mortality, indexed (standard care = 100)
-18.7%
Standard care
With AI alert confirmed within 3 hours
18.7% relative reduction in in-hospital mortality.
Source: Adams et al., Nature Medicine, 2022. TREWS system, 590,736 patients monitored across 5 hospitals.
What these numbers mean
None of these studies used HiNow models, and that is exactly why they are here: they are the public, independent ruler of what frontier AI already does when it is used to help. Detecting earlier, watching what humans do not have the arms to watch, and giving doctors back the time that bureaucracy eats.
This is the side of the technology we chose. Vision models that read exams and documents exist today at any scale, and what separates benefit from waste is not the size of the model: it is the model living inside the real workflow, with validation and human approval. That is the work we do every day.
