NLP in Healthcare and Life Sciences Market (By Component: Solutions, Services; By NLP Type; By Deployment Mode; By Organization Size; By Application; By NLP Technique; By End User)- Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2023-2032

The global NLP in healthcare and life sciences market was valued at USD 2.39 billion in 2022 and it is predicted to surpass around USD 26.75 billion by 2032 with a CAGR of 27.3% from 2023 to 2032.

NLP in Healthcare and Life Sciences Market Size 2023 to 2032

Key Pointers

  • The solution segment is expected to account for a larger market size during the forecast period.
  • By the application segment, Automated Registry Reporting segment to register the highest CAGR during the forecast period.
  • Based on organization size, the market share of large enterprises is higher; however, the market for SMEs is expected to increase at a higher CAGR during the forecast period.
  • North America is expected to have the largest market share in the NLP in healthcare and life sciences market.
  • APAC to have a higher CAGR during the forecast period.

Report Scope of the NLP in Healthcare and Life Sciences Market

Report Coverage Details
Market Size in 2022 USD 2.39 billion
Revenue Forecast by 2032 USD 26.75 billion
Growth rate from 2023 to 2032 CAGR of 27.3%
Base Year 2022
Forecast Period 2023 to 2032
Regions Covered North America, Europe, Asia Pacific, Latin America, Middle East & Africa
Companies Covered 3M Company, Alphabet Inc., Amazon.com, Inc., Averbis GmbH, Cerner Corporation, Clinithink, Conversica Inc., Dolbey Systems, Inc., Health Fidelity, Inc., Hewlett Packard Enterprise Development LP, IBM Corporation, Inovalon, IQVIA Holdings Inc., Lexalytics, Microsoft Corporation, SparkCognition, and Wave Health Technologies.

 

NLP is frequently utilized in the healthcare and life sciences as it can extract data from enormous amounts of clinical data and refine it for better physician preparation and assessment. Doctors may spend as much time with their patients and give them their full attention due to the natural language processing platform.

Several clinicians prefer printed or typed voice notes. As a result, the natural language processing platform may be utilized to analyze speech and update data accurately. Unstructured data in real-world data sources like EHRs, patient forums, and other sources make extracting usable insights from the data challenging and time-consuming. This issue is alleviated by AI-powered natural language processing technology. Healthcare and life sciences companies use natural language processing in drug discovery, text mining EHR data, and utilizing data to produce future insights for commercial advantages, resulting in actionable insights that improve care and efficacy.

The NLP in healthcare and life sciences market is driven by the rising public and private R&D investment in the natural language processing platforms. For instance, in August 2021, the Denmark government focused on strengthening research and development for natural language processing in healthcare and life sciences. NLP is a branch of linguistics and computer sciences concerned with the interactions of systems, and human language is a key component in the development and application of artificial intelligence (AI). However, because only about six million people understand Danish, solutions based solely on the danish language are ineffective.

Growth Drivers

The natural language processing in healthcare and life sciences market has observed extensive developments in the last few decades, supported by factors such as the rising market demand for enhanced customer services. Customer's market demand for better healthcare and life sciences services is expected to drive natural language processing in healthcare and life sciences market expansion.

The leading players in the global NLP in healthcare and life sciences market are focused on expanding digital technologies in the healthcare industry. Natural language processing is a subset of artificial intelligence (AI) that fosters human-machine interaction. For instance, in September 2021, Mercury natural language processing was launched by Melax Tech, an AI-powered software provider of natural language processing technology. The new software includes clinical NLP pipelines for extracting useful unstructured textual medical data for quantitative analytics in medicine and pharmaceuticals.

Mercury NLP provides quick and easy access to text data in various forms, and the program can be used in a HIPAA-compliant cloud environment or on-premise. Mercury NLP software by Melax Tech extracts text data from diagnoses, recommended medications, tests, lab results, discharge plans, and more in real-time. The technique can also be used to improve public health by analyzing social determinants of health data. These abrasive solutions reduce the number of workers needed in the healthcare and life science industry while increasing productivity in the back office and clinical environments.

NLP in Healthcare and Life Sciences Market Segmentations:

By Component By NLP Type By Deployment Mode By Organization Size

Solutions

Services

Rule-based Natural Language Processing

Statistical Natural Language Processing

Hybrid Natural Language Processing

On-premises

Cloud

Large Enterprises

SMEs

 

By Application By NLP Technique By End User

Sentiment Analysis

Drug Discovery

Clinical Trial Matching

Risk & Compliance Management

Dictation & EMR Implications

Automated Registry Reporting

AI Chatbots & Virtual Scribe

Other

Optical Character Recognition (OCR)

Interactive Voice Response (IVR)

Sentiment Analysis

Text & Speech Analytics

Image & Pattern Recognition

Text Summarization & Categorization

Other

Public Health & Government Agencies

Medical Devices

Healthcare Insurance

Pharmaceuticals

Other

Frequently Asked Questions

The global NLP in healthcare and life sciences market size was reached at USD 2.39 billion in 2022 and it is projected to hit around USD 26.75 billion by 2032.

The global NLP in healthcare and life sciences market is growing at a compound annual growth rate (CAGR) of 27.3% from 2023 to 2032.

The North America region has accounted for the largest NLP in healthcare and life sciences market share in 2022.

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. Market Dynamics Analysis and Trends

5.1. Market Dynamics

5.1.1. Market Drivers

5.1.2. Market Restraints

5.1.3. Market Opportunities

5.2. Porter’s Five Forces Analysis

5.2.1. Bargaining power of suppliers

5.2.2. Bargaining power of buyers

5.2.3. Threat of substitute

5.2.4. Threat of new entrants

5.2.5. Degree of competition

Chapter 6. Competitive Landscape

6.1.1. Company Market Share/Positioning Analysis

6.1.2. Key Strategies Adopted by Players

6.1.3. Vendor Landscape

6.1.3.1. List of Suppliers

6.1.3.2. List of Buyers

Chapter 7. Global NLP in Healthcare and Life Sciences Market, By Component

7.1. NLP in Healthcare and Life Sciences Market, by Component, 2023-2032

7.1.1. Solutions

7.1.1.1. Market Revenue and Forecast (2020-2032)

7.1.2. Services

7.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 8. Global NLP in Healthcare and Life Sciences Market, By NLP Type

8.1. NLP in Healthcare and Life Sciences Market, by NLP Type, 2023-2032

8.1.1. Rule-based Natural Language Processing

8.1.1.1. Market Revenue and Forecast (2020-2032)

8.1.2. Statistical Natural Language Processing

8.1.2.1. Market Revenue and Forecast (2020-2032)

8.1.3. Hybrid Natural Language Processing

8.1.3.1. Market Revenue and Forecast (2020-2032)

Chapter 9. Global NLP in Healthcare and Life Sciences Market, By Deployment Mode

9.1. NLP in Healthcare and Life Sciences Market, by Deployment Mode, 2023-2032

9.1.1. On-premises

9.1.1.1. Market Revenue and Forecast (2020-2032)

9.1.2. Cloud

9.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 10. Global NLP in Healthcare and Life Sciences Market, By Organization Size

10.1. NLP in Healthcare and Life Sciences Market, by Organization Size, 2023-2032

10.1.1. Large Enterprises

10.1.1.1. Market Revenue and Forecast (2020-2032)

10.1.2. SMEs

10.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 11. Global NLP in Healthcare and Life Sciences Market, By Application

11.1. NLP in Healthcare and Life Sciences Market, by Application, 2023-2032

11.1.1. Sentiment Analysis

11.1.1.1. Market Revenue and Forecast (2020-2032)

11.1.2. Drug Discovery

11.1.2.1. Market Revenue and Forecast (2020-2032)

11.1.3. Clinical Trial Matching

11.1.3.1. Market Revenue and Forecast (2020-2032)

11.1.4. Risk & Compliance Management

11.1.4.1. Market Revenue and Forecast (2020-2032)

11.1.5. Dictation & EMR Implications

11.1.5.1. Market Revenue and Forecast (2020-2032)

11.1.6. Automated Registry Reporting

11.1.6.1. Market Revenue and Forecast (2020-2032)

11.1.7. AI Chatbots & Virtual Scribe

11.1.7.1. Market Revenue and Forecast (2020-2032)

11.1.8. Others

11.1.8.1. Market Revenue and Forecast (2020-2032)

Chapter 12. Global NLP in Healthcare and Life Sciences Market, By NLP Technique

12.1. NLP in Healthcare and Life Sciences Market, by NLP Technique, 2023-2032

12.1.1. Optical Character Recognition (OCR)

12.1.1.1. Market Revenue and Forecast (2020-2032)

12.1.2. Interactive Voice Response (IVR)

12.1.2.1. Market Revenue and Forecast (2020-2032)

12.1.3. Sentiment Analysis

12.1.3.1. Market Revenue and Forecast (2020-2032)

12.1.4. Text & Speech Analytics

12.1.4.1. Market Revenue and Forecast (2020-2032)

12.1.5. Image & Pattern Recognition

12.1.5.1. Market Revenue and Forecast (2020-2032)

12.1.6. Text Summarization & Categorization

12.1.6.1. Market Revenue and Forecast (2020-2032)

12.1.7. Others

12.1.7.1. Market Revenue and Forecast (2020-2032)

Chapter 13. Global NLP in Healthcare and Life Sciences Market, By End User

13.1. NLP in Healthcare and Life Sciences Market, by End User, 2023-2032

13.1.1. Public Health & Government Agencies

13.1.1.1. Market Revenue and Forecast (2020-2032)

13.1.2. Medical Devices

13.1.2.1. Market Revenue and Forecast (2020-2032)

13.1.3. Healthcare Insurance

13.1.3.1. Market Revenue and Forecast (2020-2032)

13.1.4. Pharmaceuticals

13.1.4.1. Market Revenue and Forecast (2020-2032)

13.1.5. Others

13.1.5.1. Market Revenue and Forecast (2020-2032)

Chapter 14. Global NLP in Healthcare and Life Sciences Market, Regional Estimates and Trend Forecast

14.1. North America

14.1.1. Market Revenue and Forecast, by Component (2020-2032)

14.1.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.1.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.1.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.1.5. Market Revenue and Forecast, by Application (2020-2032)

14.1.6. Market Revenue and Forecast, by End User (2020-2032)

14.1.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.1.8. U.S.

14.1.8.1. Market Revenue and Forecast, by Component (2020-2032)

14.1.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.1.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.1.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.1.8.5. Market Revenue and Forecast, by Application (2020-2032)

14.1.8.6. Market Revenue and Forecast, by End User (2020-2032)

14.1.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.1.9. Rest of North America

14.1.9.1. Market Revenue and Forecast, by Component (2020-2032)

14.1.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.1.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.1.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.1.9.5. Market Revenue and Forecast, by Application (2020-2032)

14.1.9.6. Market Revenue and Forecast, by End User (2020-2032)

14.1.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.2. Europe

14.2.1. Market Revenue and Forecast, by Component (2020-2032)

14.2.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.2.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.2.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.2.5. Market Revenue and Forecast, by Application (2020-2032)

14.2.6. Market Revenue and Forecast, by End User (2020-2032)

14.2.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.2.8. UK

14.2.8.1. Market Revenue and Forecast, by Component (2020-2032)

14.2.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.2.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.2.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.2.8.5. Market Revenue and Forecast, by Application (2020-2032)

14.2.8.6. Market Revenue and Forecast, by End User (2020-2032)

14.2.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.2.9. Germany

14.2.9.1. Market Revenue and Forecast, by Component (2020-2032)

14.2.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.2.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.2.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.2.9.5. Market Revenue and Forecast, by Application (2020-2032)

14.2.9.6. Market Revenue and Forecast, by End User (2020-2032)

14.2.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.2.10. France

14.2.10.1. Market Revenue and Forecast, by Component (2020-2032)

14.2.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.2.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.2.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.2.10.5. Market Revenue and Forecast, by Application (2020-2032)

14.2.10.6. Market Revenue and Forecast, by End User (2020-2032)

14.2.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.2.11. Rest of Europe

14.2.11.1. Market Revenue and Forecast, by Component (2020-2032)

14.2.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.2.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.2.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.2.11.5. Market Revenue and Forecast, by Application (2020-2032)

14.2.11.6. Market Revenue and Forecast, by End User (2020-2032)

14.2.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.3. APAC

14.3.1. Market Revenue and Forecast, by Component (2020-2032)

14.3.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.3.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.3.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.3.5. Market Revenue and Forecast, by Application (2020-2032)

14.3.6. Market Revenue and Forecast, by End User (2020-2032)

14.3.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.3.8. India

14.3.8.1. Market Revenue and Forecast, by Component (2020-2032)

14.3.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.3.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.3.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.3.8.5. Market Revenue and Forecast, by Application (2020-2032)

14.3.8.6. Market Revenue and Forecast, by End User (2020-2032)

14.3.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.3.9. China

14.3.9.1. Market Revenue and Forecast, by Component (2020-2032)

14.3.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.3.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.3.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.3.9.5. Market Revenue and Forecast, by Application (2020-2032)

14.3.9.6. Market Revenue and Forecast, by End User (2020-2032)

14.3.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.3.10. Japan

14.3.10.1. Market Revenue and Forecast, by Component (2020-2032)

14.3.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.3.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.3.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.3.10.5. Market Revenue and Forecast, by Application (2020-2032)

14.3.10.6. Market Revenue and Forecast, by End User (2020-2032)

14.3.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.3.11. Rest of APAC

14.3.11.1. Market Revenue and Forecast, by Component (2020-2032)

14.3.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.3.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.3.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.3.11.5. Market Revenue and Forecast, by Application (2020-2032)

14.3.11.6. Market Revenue and Forecast, by End User (2020-2032)

14.3.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.4. MEA

14.4.1. Market Revenue and Forecast, by Component (2020-2032)

14.4.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.4.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.4.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.4.5. Market Revenue and Forecast, by Application (2020-2032)

14.4.6. Market Revenue and Forecast, by End User (2020-2032)

14.4.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.4.8. GCC

14.4.8.1. Market Revenue and Forecast, by Component (2020-2032)

14.4.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.4.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.4.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.4.8.5. Market Revenue and Forecast, by Application (2020-2032)

14.4.8.6. Market Revenue and Forecast, by End User (2020-2032)

14.4.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.4.9. North Africa

14.4.9.1. Market Revenue and Forecast, by Component (2020-2032)

14.4.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.4.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.4.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.4.9.5. Market Revenue and Forecast, by Application (2020-2032)

14.4.9.6. Market Revenue and Forecast, by End User (2020-2032)

14.4.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.4.10. South Africa

14.4.10.1. Market Revenue and Forecast, by Component (2020-2032)

14.4.10.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.4.10.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.4.10.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.4.10.5. Market Revenue and Forecast, by Application (2020-2032)

14.4.10.6. Market Revenue and Forecast, by End User (2020-2032)

14.4.10.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.4.11. Rest of MEA

14.4.11.1. Market Revenue and Forecast, by Component (2020-2032)

14.4.11.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.4.11.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.4.11.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.4.11.5. Market Revenue and Forecast, by Application (2020-2032)

14.4.11.6. Market Revenue and Forecast, by End User (2020-2032)

14.4.11.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.5. Latin America

14.5.1. Market Revenue and Forecast, by Component (2020-2032)

14.5.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.5.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.5.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.5.5. Market Revenue and Forecast, by Application (2020-2032)

14.5.6. Market Revenue and Forecast, by End User (2020-2032)

14.5.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.5.8. Brazil

14.5.8.1. Market Revenue and Forecast, by Component (2020-2032)

14.5.8.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.5.8.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.5.8.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.5.8.5. Market Revenue and Forecast, by Application (2020-2032)

14.5.8.6. Market Revenue and Forecast, by End User (2020-2032)

14.5.8.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

14.5.9. Rest of LATAM

14.5.9.1. Market Revenue and Forecast, by Component (2020-2032)

14.5.9.2. Market Revenue and Forecast, by NLP Type (2020-2032)

14.5.9.3. Market Revenue and Forecast, by Deployment Mode (2020-2032)

14.5.9.4. Market Revenue and Forecast, by Organization Size (2020-2032)

14.5.9.5. Market Revenue and Forecast, by Application (2020-2032)

14.5.9.6. Market Revenue and Forecast, by End User (2020-2032)

14.5.9.7. Market Revenue and Forecast, by NLP Technique (2020-2032)

Chapter 15. Company Profiles

15.1. 3M Company

15.1.1. Company Overview

15.1.2. Product Offerings

15.1.3. Financial Performance

15.1.4. Recent Initiatives

15.2. Alphabet Inc.

15.2.1. Company Overview

15.2.2. Product Offerings

15.2.3. Financial Performance

15.2.4. Recent Initiatives

15.3. Amazon.com, Inc.

15.3.1. Company Overview

15.3.2. Product Offerings

15.3.3. Financial Performance

15.3.4. Recent Initiatives

15.4. Averbis GmbH

15.4.1. Company Overview

15.4.2. Product Offerings

15.4.3. Financial Performance

15.4.4. Recent Initiatives

15.5. Cerner Corporation

15.5.1. Company Overview

15.5.2. Product Offerings

15.5.3. Financial Performance

15.5.4. Recent Initiatives

15.6. Clinithink

15.6.1. Company Overview

15.6.2. Product Offerings

15.6.3. Financial Performance

15.6.4. Recent Initiatives

15.7. Conversica Inc.

15.7.1. Company Overview

15.7.2. Product Offerings

15.7.3. Financial Performance

15.7.4. Recent Initiatives

15.8. Dolbey Systems, Inc.

15.8.1. Company Overview

15.8.2. Product Offerings

15.8.3. Financial Performance

15.8.4. Recent Initiatives

15.9. Health Fidelity, Inc.

15.9.1. Company Overview

15.9.2. Product Offerings

15.9.3. Financial Performance

15.9.4. Recent Initiatives

15.10. Hewlett Packard Enterprise Development LP

15.10.1. Company Overview

15.10.2. Product Offerings

15.10.3. Financial Performance

15.10.4. Recent Initiatives

Chapter 16. Research Methodology

16.1. Primary Research

16.2. Secondary Research

16.3. Assumptions

Chapter 17. Appendix

17.1. About Us

17.2. Glossary of Terms

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