Apache Spark NLP for Healthcare - Building Real-World AI Systems

Explore real-world case studies of AI systems using Natural Language Processing (NLP) in healthcare in this 37-minute conference talk from Databricks. Gain insights into projects deploying automated patient risk prediction, diagnosis, clinical guidelines, and revenue cycle optimization. Learn why and how NLP was utilized, which deep learning models and libraries were employed, and the outcomes achieved. Discover key considerations for NLP projects, including building domain-specific healthcare models and integrating NLP into larger, scalable machine learning and deep learning pipelines in distributed environments. Delve into topics such as Spark NLP, healthcare data sources, recognition models, clinical models, and specific case studies involving spell checking, entity recognition, and ICD-10 code assignment. Acquire valuable knowledge on implementing NLP in healthcare AI systems and understand the potential impact on various aspects of the healthcare industry.

Introduction
Introduction to Spark NLP
What is Spark NLP
Spark Enterprise and Spark Public
Trusted Companies
Supported Languages
Survey Results
Building Pipelines
Pipeline Overview
Spark NLP Overview
Spark NLP Developer
Healthcare Data
Data Sources
Language
Dataset
Extract
Healthcare Models
Recognition Model
Coefficient Models
Comparison
Negativity Scope
Clinical Model
Normalized Code
Case Studies
Select Data
SpellChecker
Entities
Assigning ICD10 Codes
Rush Company
PDF
SODOR
SLOW
Nurse Staffing
Clinical Trials
Lookup Tables
Results by Dots
Resources