In the era of large language models (LLMs)—where generative AI can write, summarize, translate, and even reason across complex documents—the function of data annotation has shifted dramatically. What was once a preparatory task for training AI is now a core part of a continuous feedback and improvement cycle.
In the era of large language models (LLMs)—where generative AI can write, summarize, translate, and even reason across complex documents—the function of data annotation has shifted dramatically. What was once...
Introduction Healthcare organizations are under increasing pressure to improve the accuracy and efficiency of clinical documentation and risk adjustment. With the rise of value-based care, Hierarchical Condition Category (HCC) coding...
Enhancing Risk Adjustment Accuracy and Revenue Integrity with AI-Powered HCC Coding In April, the Centers for Medicare & Medicaid Services (CMS) released its 2026 Medicare Advantage (MA) Rate Announcement, projecting...
GLiNER and OpenPipe Shine on General Texts but Miss Over 50% of Clinical PHI — Compared to Less Than 5% Misses by Solutions Like John Snow Labs It’s often assumed...
Effortless Clinical Text Analysis with Advanced Pretrained Pipelines This blog post explores Healthcare NLP’s Task-Based Clinical Pretrained Pipelines, showcasing how they streamline clinical text analysis with just one-liner codes. By...
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