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시장보고서
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의료용 자연언어처리(NLP) : 세계 시장 점유율과 순위, 총판매량 및 수요 예측(2025-2031년)

Natural Language Processing (NLP) in Healthcare - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031
발행일: | 리서치사: QYResearch | 페이지 정보: 영문 | 배송안내 : 2-3일 (영업일 기준)

    
    
    




■ 보고서에 따라 최신 정보로 업데이트하여 보내드립니다. 배송일정은 문의해 주시기 바랍니다.

세계의 의료용 자연언어처리(NLP) 시장 규모는 2024년에 12억 2,500만 달러로 추정되며, 2025-2031년의 예측 기간 중 CAGR 13.6%로 성장하며, 2031년까지 30억 2,400만 달러로 확대할 것으로 예측됩니다.

자연 언어처리(NLP)는 인공지능의 한 분야로, 자바나 C++ 등의 인공언어가 아닌 자연 언어(구어 또는 문어 데이터)를 이용한 컴퓨터와 인간의 상호작용을 다루는 기술입니다.

NLP의 궁극적인 목적은 인간의 언어를 읽고, 해독하고, 이해하고, 가치 있는 형태로 의미를 추출하는 것입니다. 대부분의 NLP 기술은 인간의 언어에서 의미를 도출하기 위해 머신러닝에 의존하고 있습니다.

의료 분야에서 NLP는 환자와의 교감을 강화하고 의사결정 능력의 효율성을 높이기 위해 활용됩니다. 또한 복잡한 임상 기록을 실용적인 데이터 포인트와 인사이트으로 변환할 수 있습니다.

자연 언어 처리(NLP)는 1950년대에 처음 개발되었으며, 지난 25년 동안 저렴하고 고성능의 컴퓨터가 병렬 처리가 가능해지면서 급속도로 발전했습니다.

의료산업은 NLP의 적용에 더욱 많은 노력이 필요한 특수한 산업입니다. 그 이유는 실용적으로 영어를 위해 구축된 기성 NLP 라이브러리와 알고리즘이 의료 산업의 '다른 언어'에서는 전혀 작동하지 않기 때문입니다.

예를 들어 의료 분야에서 SoB(Shortness of Breath)는 '숨가쁨'을 의미합니다. 이러한 지식이 없으면 환자의 보고서나 문서를 이해하기 어렵고, 적절한 판단을 내리기도 어렵습니다.

동시에 의료 데이터의 약 80%가 비정형 데이터로 존재하며, 정형 데이터로 변환이 필요하다는 조사 결과도 있습니다. 따라서 의료 분야에서의 NLP는 전문적인 의료 언어와 텍스트 서비스를 필요로 하는 매우 유망하면서도 매우 도전적인 산업입니다.

이 보고서는 세계의 의료 분야 자연 언어처리(NLP) 시장에 대해 총매출액, 주요 기업의 시장 점유율 및 순위를 중심으로 지역별, 국가별, 유형별, 용도별 분석을 종합적으로 제시하는 것을 목적으로 합니다.

의료 분야의 자연 언어처리(NLP) 시장 규모, 추정치, 예측치를 매출액 기준으로 제시하고, 2024년을 기준 연도로 하여 2020-2031년 기간의 과거 데이터와 예측 데이터를 포함하고 있습니다. 정량적, 정성적 분석을 통해 독자들이 비즈니스/성장 전략을 수립하고, 시장 경쟁 구도를 평가하고, 현재 시장에서의 위치를 분석하고, 의료 분야의 자연 언어처리(NLP)에 대한 정보에 입각한 비즈니스 의사결정을 내릴 수 있도록 돕습니다.

시장 세분화

기업별

  • Solventum
  • Linguamatics
  • Amazon AWS
  • SAS
  • IBM
  • Microsoft(Nuance)
  • Averbis
  • Edifecs(Health Fidelity)
  • Dolbey Systems

유형별 부문

  • 기계 번역
  • 정보 추출
  • 자동 요약
  • 텍스트 및 음성 처리
  • 기타

용도별 부문

  • 전자건강기록(EHR)
  • CAC(Computer-Assisted Coding)
  • 임상의 문서
  • 기타

지역별

  • 북미
    • 미국
    • 캐나다
  • 아시아태평양
    • 중국
    • 일본
    • 한국
    • 동남아시아
    • 인도
    • 호주
    • 기타 아시아태평양
  • 유럽
    • 독일
    • 프랑스
    • 영국
    • 이탈리아
    • 네덜란드
    • 북유럽 국가
    • 기타 유럽
  • 라틴아메리카
    • 멕시코
    • 브라질
    • 기타 라틴아메리카
  • 중동 및 아프리카
    • 튀르키예
    • 사우디아라비아
    • 아랍에미리트
    • 기타 중동 및 아프리카
KSA 25.12.05

자주 묻는 질문

  • 의료용 자연언어처리(NLP) 시장 규모는 어떻게 예측되나요?
  • 자연 언어처리(NLP)의 주요 목적은 무엇인가요?
  • 의료 분야에서 NLP는 어떤 용도로 활용되나요?
  • 의료 산업에서 NLP의 도전 과제는 무엇인가요?
  • 의료 데이터의 비율 중 비정형 데이터는 얼마나 되나요?
  • 의료 분야의 자연 언어처리(NLP) 시장에 참여하고 있는 주요 기업은 어디인가요?
  • 의료 분야에서 NLP의 유형은 어떤 것들이 있나요?
  • 의료 분야에서 NLP의 용도는 무엇인가요?

The global market for Natural Language Processing (NLP) in Healthcare was estimated to be worth US$ 1225 million in 2024 and is forecast to a readjusted size of US$ 3024 million by 2031 with a CAGR of 13.6% during the forecast period 2025-2031.

Natural language processing (NLP) is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language (spoken or written data), not in the artificial languages such as Java and C++.

The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Most NLP techniques rely on machine learning to derive meaning from human languages.

For healthcare use, NLP is used to improve patient engagement and bring in efficiency in decision-making capabilities, it can also convert complex clinical narratives into actionable data points and insights.

Natural Language Processing (NLP) is first developed in the 1950s, it has blossomed over the past 25 years with the availability of cheap, plentiful, and powerful computers working in parallel fashion.

Healthcare industry is a unique industry that need put more effort on the application of NLP, it is because in practice, off-the-shelf NLP libraries and algorithms built for English will fail miserably on this "different language" in the health care industry.

For example, SoB in healthcare means short of breath. If you don't know that, it is hard to understand one patient's the report or document then difficult to make decision.

At the same time, there are research show that about 80% of medical data is showed in unstructured format, which need to get structured data conversion, so NLP in healthcare is an a very promising but very challenging industry that requires specialized medical language and text services.

This report aims to provide a comprehensive presentation of the global market for Natural Language Processing (NLP) in Healthcare, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Natural Language Processing (NLP) in Healthcare by region & country, by Type, and by Application.

The Natural Language Processing (NLP) in Healthcare market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Natural Language Processing (NLP) in Healthcare.

Market Segmentation

By Company

  • Solventum
  • Linguamatics
  • Amazon AWS
  • SAS
  • IBM
  • Microsoft (Nuance)
  • Averbis
  • Edifecs (Health Fidelity)
  • Dolbey Systems

Segment by Type

  • Machine Translation
  • Information Extraction
  • Automatic Summarization
  • Text and Voice Processing
  • Other

Segment by Application

  • Electronic Health Records (EHR)
  • Computer-Assisted Coding (CAC)
  • Clinician Document
  • Other

By Region

  • North America
    • United States
    • Canada
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • Southeast Asia
    • India
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • U.K.
    • Italy
    • Netherlands
    • Nordic Countries
    • Rest of Europe
  • Latin America
    • Mexico
    • Brazil
    • Rest of Latin America
  • Middle East & Africa
    • Turkey
    • Saudi Arabia
    • UAE
    • Rest of MEA

Chapter Outline

Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 2: Detailed analysis of Natural Language Processing (NLP) in Healthcare company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.

Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 5: Revenue of Natural Language Processing (NLP) in Healthcare in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.

Chapter 6: Revenue of Natural Language Processing (NLP) in Healthcare in country level. It provides sigmate data by Type, and by Application for each country/region.

Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.

Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.

Chapter 9: Conclusion.

Table of Contents

1 Market Overview

  • 1.1 Natural Language Processing (NLP) in Healthcare Product Introduction
  • 1.2 Global Natural Language Processing (NLP) in Healthcare Market Size Forecast (2020-2031)
  • 1.3 Natural Language Processing (NLP) in Healthcare Market Trends & Drivers
    • 1.3.1 Natural Language Processing (NLP) in Healthcare Industry Trends
    • 1.3.2 Natural Language Processing (NLP) in Healthcare Market Drivers & Opportunity
    • 1.3.3 Natural Language Processing (NLP) in Healthcare Market Challenges
    • 1.3.4 Natural Language Processing (NLP) in Healthcare Market Restraints
  • 1.4 Assumptions and Limitations
  • 1.5 Study Objectives
  • 1.6 Years Considered

2 Competitive Analysis by Company

  • 2.1 Global Natural Language Processing (NLP) in Healthcare Players Revenue Ranking (2024)
  • 2.2 Global Natural Language Processing (NLP) in Healthcare Revenue by Company (2020-2025)
  • 2.3 Key Companies Natural Language Processing (NLP) in Healthcare Manufacturing Base Distribution and Headquarters
  • 2.4 Key Companies Natural Language Processing (NLP) in Healthcare Product Offered
  • 2.5 Key Companies Time to Begin Mass Production of Natural Language Processing (NLP) in Healthcare
  • 2.6 Natural Language Processing (NLP) in Healthcare Market Competitive Analysis
    • 2.6.1 Natural Language Processing (NLP) in Healthcare Market Concentration Rate (2020-2025)
    • 2.6.2 Global 5 and 10 Largest Companies by Natural Language Processing (NLP) in Healthcare Revenue in 2024
    • 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Natural Language Processing (NLP) in Healthcare as of 2024)
  • 2.7 Mergers & Acquisitions, Expansion

3 Segmentation by Type

  • 3.1 Introduction by Type
    • 3.1.1 Machine Translation
    • 3.1.2 Information Extraction
    • 3.1.3 Automatic Summarization
    • 3.1.4 Text and Voice Processing
    • 3.1.5 Other
  • 3.2 Global Natural Language Processing (NLP) in Healthcare Sales Value by Type
    • 3.2.1 Global Natural Language Processing (NLP) in Healthcare Sales Value by Type (2020 VS 2024 VS 2031)
    • 3.2.2 Global Natural Language Processing (NLP) in Healthcare Sales Value, by Type (2020-2031)
    • 3.2.3 Global Natural Language Processing (NLP) in Healthcare Sales Value, by Type (%) (2020-2031)

4 Segmentation by Application

  • 4.1 Introduction by Application
    • 4.1.1 Electronic Health Records (EHR)
    • 4.1.2 Computer-Assisted Coding (CAC)
    • 4.1.3 Clinician Document
    • 4.1.4 Other
  • 4.2 Global Natural Language Processing (NLP) in Healthcare Sales Value by Application
    • 4.2.1 Global Natural Language Processing (NLP) in Healthcare Sales Value by Application (2020 VS 2024 VS 2031)
    • 4.2.2 Global Natural Language Processing (NLP) in Healthcare Sales Value, by Application (2020-2031)
    • 4.2.3 Global Natural Language Processing (NLP) in Healthcare Sales Value, by Application (%) (2020-2031)

5 Segmentation by Region

  • 5.1 Global Natural Language Processing (NLP) in Healthcare Sales Value by Region
    • 5.1.1 Global Natural Language Processing (NLP) in Healthcare Sales Value by Region: 2020 VS 2024 VS 2031
    • 5.1.2 Global Natural Language Processing (NLP) in Healthcare Sales Value by Region (2020-2025)
    • 5.1.3 Global Natural Language Processing (NLP) in Healthcare Sales Value by Region (2026-2031)
    • 5.1.4 Global Natural Language Processing (NLP) in Healthcare Sales Value by Region (%), (2020-2031)
  • 5.2 North America
    • 5.2.1 North America Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 5.2.2 North America Natural Language Processing (NLP) in Healthcare Sales Value by Country (%), 2024 VS 2031
  • 5.3 Europe
    • 5.3.1 Europe Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 5.3.2 Europe Natural Language Processing (NLP) in Healthcare Sales Value by Country (%), 2024 VS 2031
  • 5.4 Asia Pacific
    • 5.4.1 Asia Pacific Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 5.4.2 Asia Pacific Natural Language Processing (NLP) in Healthcare Sales Value by Region (%), 2024 VS 2031
  • 5.5 South America
    • 5.5.1 South America Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 5.5.2 South America Natural Language Processing (NLP) in Healthcare Sales Value by Country (%), 2024 VS 2031
  • 5.6 Middle East & Africa
    • 5.6.1 Middle East & Africa Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 5.6.2 Middle East & Africa Natural Language Processing (NLP) in Healthcare Sales Value by Country (%), 2024 VS 2031

6 Segmentation by Key Countries/Regions

  • 6.1 Key Countries/Regions Natural Language Processing (NLP) in Healthcare Sales Value Growth Trends, 2020 VS 2024 VS 2031
  • 6.2 Key Countries/Regions Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
  • 6.3 United States
    • 6.3.1 United States Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.3.2 United States Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.3.3 United States Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.4 Europe
    • 6.4.1 Europe Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.4.2 Europe Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.4.3 Europe Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.5 China
    • 6.5.1 China Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.5.2 China Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.5.3 China Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.6 Japan
    • 6.6.1 Japan Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.6.2 Japan Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.6.3 Japan Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.7 South Korea
    • 6.7.1 South Korea Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.7.2 South Korea Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.7.3 South Korea Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.8 Southeast Asia
    • 6.8.1 Southeast Asia Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.8.2 Southeast Asia Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.8.3 Southeast Asia Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031
  • 6.9 India
    • 6.9.1 India Natural Language Processing (NLP) in Healthcare Sales Value, 2020-2031
    • 6.9.2 India Natural Language Processing (NLP) in Healthcare Sales Value by Type (%), 2024 VS 2031
    • 6.9.3 India Natural Language Processing (NLP) in Healthcare Sales Value by Application, 2024 VS 2031

7 Company Profiles

  • 7.1 Solventum
    • 7.1.1 Solventum Profile
    • 7.1.2 Solventum Main Business
    • 7.1.3 Solventum Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.1.4 Solventum Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.1.5 Solventum Recent Developments
  • 7.2 Linguamatics
    • 7.2.1 Linguamatics Profile
    • 7.2.2 Linguamatics Main Business
    • 7.2.3 Linguamatics Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.2.4 Linguamatics Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.2.5 Linguamatics Recent Developments
  • 7.3 Amazon AWS
    • 7.3.1 Amazon AWS Profile
    • 7.3.2 Amazon AWS Main Business
    • 7.3.3 Amazon AWS Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.3.4 Amazon AWS Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.3.5 Amazon AWS Recent Developments
  • 7.4 SAS
    • 7.4.1 SAS Profile
    • 7.4.2 SAS Main Business
    • 7.4.3 SAS Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.4.4 SAS Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.4.5 SAS Recent Developments
  • 7.5 IBM
    • 7.5.1 IBM Profile
    • 7.5.2 IBM Main Business
    • 7.5.3 IBM Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.5.4 IBM Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.5.5 IBM Recent Developments
  • 7.6 Microsoft (Nuance)
    • 7.6.1 Microsoft (Nuance) Profile
    • 7.6.2 Microsoft (Nuance) Main Business
    • 7.6.3 Microsoft (Nuance) Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.6.4 Microsoft (Nuance) Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.6.5 Microsoft (Nuance) Recent Developments
  • 7.7 Averbis
    • 7.7.1 Averbis Profile
    • 7.7.2 Averbis Main Business
    • 7.7.3 Averbis Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.7.4 Averbis Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.7.5 Averbis Recent Developments
  • 7.8 Edifecs (Health Fidelity)
    • 7.8.1 Edifecs (Health Fidelity) Profile
    • 7.8.2 Edifecs (Health Fidelity) Main Business
    • 7.8.3 Edifecs (Health Fidelity) Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.8.4 Edifecs (Health Fidelity) Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.8.5 Edifecs (Health Fidelity) Recent Developments
  • 7.9 Dolbey Systems
    • 7.9.1 Dolbey Systems Profile
    • 7.9.2 Dolbey Systems Main Business
    • 7.9.3 Dolbey Systems Natural Language Processing (NLP) in Healthcare Products, Services and Solutions
    • 7.9.4 Dolbey Systems Natural Language Processing (NLP) in Healthcare Revenue (US$ Million) & (2020-2025)
    • 7.9.5 Dolbey Systems Recent Developments

8 Industry Chain Analysis

  • 8.1 Natural Language Processing (NLP) in Healthcare Industrial Chain
  • 8.2 Natural Language Processing (NLP) in Healthcare Upstream Analysis
    • 8.2.1 Key Raw Materials
    • 8.2.2 Raw Materials Key Suppliers
    • 8.2.3 Manufacturing Cost Structure
  • 8.3 Midstream Analysis
  • 8.4 Downstream Analysis (Customers Analysis)
  • 8.5 Sales Model and Sales Channels
    • 8.5.1 Natural Language Processing (NLP) in Healthcare Sales Model
    • 8.5.2 Sales Channel
    • 8.5.3 Natural Language Processing (NLP) in Healthcare Distributors

9 Research Findings and Conclusion

10 Appendix

  • 10.1 Research Methodology
    • 10.1.1 Methodology/Research Approach
      • 10.1.1.1 Research Programs/Design
      • 10.1.1.2 Market Size Estimation
      • 10.1.1.3 Market Breakdown and Data Triangulation
    • 10.1.2 Data Source
      • 10.1.2.1 Secondary Sources
      • 10.1.2.2 Primary Sources
  • 10.2 Author Details
  • 10.3 Disclaimer
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