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1
Introduction
2
Introduction to Spark NLP
3
What is Spark NLP
4
Spark Enterprise and Spark Public
5
Trusted Companies
6
Supported Languages
7
Survey Results
8
Building Pipelines
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Pipeline Overview
10
Spark NLP Overview
11
Spark NLP Developer
12
Healthcare Data
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Data Sources
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Language
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Dataset
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Extract
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Healthcare Models
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Recognition Model
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Coefficient Models
20
Comparison
21
Negativity Scope
22
Clinical Model
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Normalized Code
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Case Studies
25
Select Data
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SpellChecker
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Entities
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Assigning ICD10 Codes
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Rush Company
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PDF
31
SODOR
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SLOW
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Nurse Staffing
34
Clinical Trials
35
Lookup Tables
36
Results by Dots
37
Resources
Description:
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.

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

Databricks
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