In our previous article, JSL Vision: State-of-the-Art Document Understanding on Your Hardware, we benchmarked JSL Vision against leading open-source vision-language models on FUNSD and OmniOCR In this follow-up, we address...
Tl; DR: This post explains why specialized pretrained PHI pipelines are often the best starting point for data scientists working with clinical text. Instead of building a custom PHI system...
TL; DR This post presents a focused update on large-scale clinical de-identification benchmarks, emphasizing pipeline design, execution strategy, and infrastructure-aware performance. Rather than treating accuracy as an isolated metric, we...
Medical AI projects routinely deal with scanned documents and images that contain sensitive patient information. Extracting insights from these visuals is crucial – but so is protecting patient privacy. Traditionally,...
Doctors are taught a simple rule early in their training: When you hear hoofbeats, think horses, not zebras. In other words, the most common explanation is usually the right one....
Demos
See More