Comparing clinical de-identification pipelines in Spark NLP for speed and accuracy, covering NER, hybrid, and zero-shot approaches on CPU and GPU infrastructures.
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...
A single short GPT-4o query consumes 0.43 Wh of electricity. Scale that to 700 million queries per day, and the annual electricity consumption equals 35,000 U.S. residential households, or 50...
Visual de-identification is the process of detecting and masking protected health information (PHI) inside scanned medical documents, images, and PDFs. PHI in visual documents can appear in printed headers, stamps,...
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....
How is AI improving hospital capacity forecasting? Hospital systems face constant pressure to balance patient demand with finite resources. AI-driven capacity forecasting provides hospitals with the predictive intelligence needed to...
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