In assigning ICD10-CM codes, Spark NLP for Healthcare achieved a 76% success rate, while GPT-3.5 and GPT-4 had overall accuracies of 26% and 36% respectively.
In assigning ICD10-CM codes, Spark NLP for Healthcare achieved a 76% success rate, while GPT-3.5 and GPT-4 had overall accuracies of 26% and 36% respectively. Introduction In the healthcare industry,...
In this post, we explore the utilization of pre-trained models within the Healthcare NLP library by John Snow Labs to map medical terminology to the MedDRA ontology. Specifically, our aim...
How is AI transforming the shift from one-size-fits-all to precision medicine? Traditional medicine treats populations broadly, often overlooking how individual genetics influence treatment response. This approach limits efficacy and contributes...
What Is Driving the Need for AI-Powered Chronic Care Monitoring? Six in ten Americans live with at least one chronic condition1. This growing burden translates into rising healthcare costs, increasing...
The healthcare industry is approaching a defining moment. Artificial intelligence (AI), once a futuristic promise, is now becoming foundational to hospital operations. As AI capabilities evolve and regulatory frameworks mature,...
Demos
See More