Natural Language Processing Nlp In Healthcare Market Size, Type Analysis, Application Analysis, End-Use, Industry Analysis, Regional Outlook, Competitive Strategies And Forecasts, 2023-2032

  • Report ID: ME_0073873
  • Format: Electronic (PDF)
  • Publish Type: Publish
  • Number of Pages: 250
Home Healthcare natural language processing nlp....
  • Single User $3500
  • Multi User $4500
  • Enterprise User $5500
Report Description Table Of Content Research Methodology Download Free Sample

Market Snapshot

CAGR:7.2
2023
2032

Source: Market Expertz

RND-Favicon
Study Period 2019-2032
Base Year 2023
Forcast Year 2023-2032
CAGR 7.2
Healthcare-companies
Healthcare-Snapshot

Gain accurate insights regarding the negative impacts of COVID-19 on all markets and industries

Download Sample Pdf
Download Sample Pdf

Report Overview

Natural Language Processing (NLP) in Healthcare Market Analysis Report 2023-2032

The Natural Language Processing (NLP) in Healthcare Market is projected to experience a Compound Annual Growth Rate (CAGR) of 7.92% between 2022 and 2032. During this period, the market size is anticipated to witness an increase by USD 6,254.78 million. The growth of this market is influenced by various factors, including the increasing adoption of digital health solutions, the need for efficient healthcare data management, and the potential for improving patient outcomes through NLP applications.

Natural Language Processing (NLP) in Healthcare Market Overview

Drivers

One of the primary drivers propelling the growth of the NLP in Healthcare Market is the increasing adoption of digital health solutions. Healthcare providers are recognizing the value of leveraging NLP technology to extract valuable insights from unstructured clinical data. NLP can help in processing and analyzing vast amounts of textual patient records, medical literature, and notes, thereby aiding in clinical decision support and research.

Moreover, NLP plays a pivotal role in improving healthcare data management. With the exponential growth of electronic health records (EHRs) and health-related documents, the ability to efficiently extract, organize, and access information is crucial. NLP systems enable healthcare organizations to sift through this data efficiently, making it more accessible and useful for healthcare professionals.

Trends

A noteworthy trend shaping the NLP in Healthcare Market is the integration of NLP capabilities into telehealth and remote patient monitoring platforms. As telehealth services expand, there is a growing need to process and analyze patient-doctor interactions, which are often recorded as textual data. NLP can be used to extract clinical insights from these interactions, enhancing telehealth's diagnostic and treatment capabilities.

Furthermore, the use of NLP in healthcare research and clinical trials is gaining momentum. Researchers are leveraging NLP to analyze medical literature, patient records, and clinical trial data to identify trends, potential drug interactions, and adverse events. This trend is expected to contribute to advancements in healthcare research and development.

Restraints

One of the significant challenges hindering the growth of the NLP in Healthcare Market is the need for data privacy and security. Healthcare data contains sensitive patient information, and the use of NLP to analyze this data must comply with strict privacy regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States. Ensuring the secure handling of patient data remains a critical concern for healthcare organizations and NLP solution providers.

Moreover, the accuracy and reliability of NLP algorithms are essential in healthcare applications. NLP systems must be continually improved to reduce errors and misinterpretations, as incorrect clinical insights can have serious consequences for patient care.

NLP in Healthcare Market Segmentation By Application

Clinical documentation represents a significant growth segment in the NLP in Healthcare Market. Clinical documentation NLP applications focus on converting spoken or written language into structured, electronic clinical notes. This streamlines the documentation process for healthcare professionals, reducing administrative burden and improving documentation accuracy.

Another vital application is disease prediction and risk assessment. NLP models can analyze patient records and clinical data to identify potential disease risks and predict patient outcomes. Early disease detection and proactive healthcare management are critical components of this application.

NLP in Healthcare Market Segmentation By Type

The speech recognition technology segment is expected to witness significant growth during the forecast period. Speech recognition NLP applications enable the conversion of spoken language into text, making it easier to document patient interactions, create clinical notes, and improve overall healthcare data accuracy.

Text analytics and sentiment analysis also play a crucial role in healthcare applications. These NLP capabilities can extract valuable insights from unstructured text data, including patient feedback, social media discussions, and medical literature.

Regional Overview:

Download the report summary now!

Request pdf Sample

North America is anticipated to contribute significantly to the global NLP in Healthcare Market growth during the forecast period. The region has a well-established healthcare infrastructure and is at the forefront of adopting digital health technologies. NLP in healthcare has witnessed rapid adoption in North America, driven by the need for efficient healthcare data management and improved patient care.

The market may have experienced temporary disruptions during the COVID-19 pandemic as healthcare providers prioritized immediate patient care. However, as healthcare systems recover and invest in digital health solutions, the demand for NLP in healthcare is expected to rebound.

NLP in Healthcare Market Customer Landscape

The NLP in Healthcare Market report provides insights into the adoption lifecycle of the market, spanning from early adopters to laggards. It analyzes adoption rates across different regions based on penetration levels. The report also delves into key purchase criteria and factors influencing price sensitivity, aiding healthcare providers and technology companies in devising effective growth strategies.

Major NLP in Healthcare Market Companies

Companies operating in the NLP in Healthcare Market are implementing diverse strategies to enhance their market presence. These strategies include strategic partnerships, mergers and acquisitions, product/service launches, geographical expansion, and technological innovations.

Sample list of major companies in the market:

  • IBM Corporation
  • Nuance Communications, Inc.
  • 3M Company
  • Cerner Corporation
  • Linguamatics
  • Health Fidelity, Inc.
  • M*Modal
  • Dolbey Systems, Inc.
  • Apixio
  • Clinithink Ltd.

Qualitative and quantitative analyses of these companies provide insights into the competitive landscape, allowing clients to understand market dynamics and assess the strengths and weaknesses of key players. The analysis categorizes companies based on their focus and dominance within the market, offering a comprehensive view of the competitive environment.

Segment Overview

The NLP in Healthcare Market report offers revenue forecasts on a global, regional, and country level, along with an analysis of trends and growth opportunities from 2019 to 2032.

Application Outlook (USD Million, 2019 - 2032)

  • Clinical Documentation
  • Disease Prediction and Risk Assessment
  • Others

Type Outlook (USD Million, 2019 - 2032)

  • Speech Recognition Technology
  • Text Analytics and Sentiment Analysis
  • Others

Geography Outlook (USD Million, 2019 - 2032)

  • North America
    • United States
    • Canada
  • Europe
    • United Kingdom
    • Germany
    • France
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • Rest of APAC
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Middle East & Africa
    • United Arab Emirates
    • South Africa
    • Rest of Middle East & Africa

Table of Contents
Chapter 1 Overview of Natural Language Processing (NLP) in Healthcare
1.1 Definition of Natural Language Processing (NLP) in Healthcare in This Report
1.2 Commercial Types of Natural Language Processing (NLP) in Healthcare
1.2.1 Rule-Based NLP
1.2.2 Statistically Based NLP
1.2.3 Mixed NLP
1.3 Downstream Application of Natural Language Processing (NLP) in Healthcare
1.3.1 Health Care
1.3.2 Life Science
1.3.3 Other
1.4 Development History of Natural Language Processing (NLP) in Healthcare
1.5 Market Status and Trend of Natural Language Processing (NLP) in Healthcare 2014-2026
1.5.1 Global Natural Language Processing (NLP) in Healthcare Market Status and Trend 2014-2026
1.5.2 Regional Natural Language Processing (NLP) in Healthcare Market Status and Trend 2014-2026
Chapter 2 Global Market Status and Forecast by Regions
2.1 Market Development of Natural Language Processing (NLP) in Healthcare 2013-2017
2.2 Production Market of Natural Language Processing (NLP) in Healthcare by Regions
2.2.1 Production Volume of Natural Language Processing (NLP) in Healthcare by Regions
2.2.2 Production Value of Natural Language Processing (NLP) in Healthcare by Regions
2.3 Demand Market of Natural Language Processing (NLP) in Healthcare by Regions
2.4 Production and Demand Status of Natural Language Processing (NLP) in Healthcare by Regions
2.4.1 Production and Demand Status of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
2.4.2 Import and Export Status of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Chapter 3 Global Market Status and Forecast by Types
3.1 Production Volume of Natural Language Processing (NLP) in Healthcare by Types
3.2 Production Value of Natural Language Processing (NLP) in Healthcare by Types
3.3 Market Forecast of Natural Language Processing (NLP) in Healthcare by Types
Chapter 4 Global Market Status and Forecast by Downstream Industry
4.1 Demand Volume of Natural Language Processing (NLP) in Healthcare by Downstream Industry
4.2 Market Forecast of Natural Language Processing (NLP) in Healthcare by Downstream Industry
Chapter 5 Market Driving Factor Analysis of Natural Language Processing (NLP) in Healthcare
5.1 Global Economy Situation and Trend Overview
5.2 Natural Language Processing (NLP) in Healthcare Downstream Industry Situation and Trend Overview
Chapter 6 Natural Language Processing (NLP) in Healthcare Market Competition Status by Major Manufacturers
6.1 Production Volume of Natural Language Processing (NLP) in Healthcare by Major Manufacturers
6.2 Production Value of Natural Language Processing (NLP) in Healthcare by Major Manufacturers
6.3 Basic Information of Natural Language Processing (NLP) in Healthcare by Major Manufacturers
6.3.1 Headquarters Location and Established Time of Natural Language Processing (NLP) in Healthcare Major Manufacturer
6.3.2 Employees and Revenue Level of Natural Language Processing (NLP) in Healthcare Major Manufacturer
6.4 Market Competition News and Trend
6.4.1 Merger, Consolidation or Acquisition News
6.4.2 Investment or Disinvestment News
6.4.3 New Product Development and Launch
Chapter 7 Natural Language Processing (NLP) in Healthcare Major Manufacturers Introduction and Market Data
7.1 3M
7.1.1 Company profile
7.1.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.1.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of 3M
7.2 CERNER
7.2.1 Company profile
7.2.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.2.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of CERNER
7.3 IBM
7.3.1 Company profile
7.3.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.3.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of IBM
7.4 MICROSOFT
7.4.1 Company profile
7.4.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.4.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of MICROSOFT
7.5 NUANCE COMMUNICATIONS
7.5.1 Company profile
7.5.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.5.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of NUANCE COMMUNICATIONS
7.6 HEATH FIDELITY
7.6.1 Company profile
7.6.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.6.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of HEATH FIDELITY
7.7 LINGUAMATICS
7.7.1 Company profile
7.7.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.7.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of LINGUAMATICS
7.8 DOLBEY SYSTEMS
7.8.1 Company profile
7.8.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.8.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of DOLBEY SYSTEMS
7.9 APIXIO
7.9.1 Company profile
7.9.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.9.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of APIXIO
7.10 MMODAL IP
7.10.1 Company profile
7.10.2 Representative Natural Language Processing (NLP) in Healthcare Product
7.10.3 Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of MMODAL IP
Chapter 8 Upstream and Downstream Market Analysis of Natural Language Processing (NLP) in Healthcare
8.1 Industry Chain of Natural Language Processing (NLP) in Healthcare
8.2 Upstream Market and Representative Companies Analysis
8.3 Downstream Market and Representative Companies Analysis
Chapter 9 Cost and Gross Margin Analysis of Natural Language Processing (NLP) in Healthcare
9.1 Cost Structure Analysis of Natural Language Processing (NLP) in Healthcare
9.2 Raw Materials Cost Analysis of Natural Language Processing (NLP) in Healthcare
9.3 Labor Cost Analysis of Natural Language Processing (NLP) in Healthcare
9.4 Manufacturing Expenses Analysis of Natural Language Processing (NLP) in Healthcare
Chapter 10 Marketing Status Analysis of Natural Language Processing (NLP) in Healthcare
10.1 Marketing Channel
10.1.1 Direct Marketing
10.1.2 Indirect Marketing
10.1.3 Marketing Channel Development Trend
10.2 Market Positioning
10.2.1 Pricing Strategy
10.2.2 Brand Strategy
10.2.3 Target Client
10.3 Distributors/Traders List
Chapter 11 Report Conclusion
Chapter 12 Research Methodology and Reference
12.1 Methodology/Research Approach
12.1.1 Research Programs/Design
12.1.2 Market Size Estimation
12.1.3 Market Breakdown and Data Triangulation
12.2 Data Source
12.2.1 Secondary Sources
12.2.2 Primary Sources
12.3 Reference



List of Tables

Table Advantage and Disadvantage of Rule-Based NLP
Table Advantage and Disadvantage of Statistically Based NLP
Table Advantage and Disadvantage of Mixed NLP
Table Production Volume of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Table Production Value of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Table Demand Volume of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Table Production and Demand Status of Natural Language Processing (NLP) in Healthcare in Region One 2013-2017
Table Production and Demand Status of Natural Language Processing (NLP) in Healthcare in Region Two 2013-2017
Table Production and Demand Status of Natural Language Processing (NLP) in Healthcare in Region Three 2013-2017
Table Production and Demand Status of Natural Language Processing (NLP) in Healthcare in Region Four 2013-2017
Table Import Volume of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Table Export Volume of Natural Language Processing (NLP) in Healthcare by Regions 2013-2017
Table Production Volume of Natural Language Processing (NLP) in Healthcare by Types 2013-2017
Table Production Value of Natural Language Processing (NLP) in Healthcare by Types 2013-2017
Table Production Volume Forecast of Natural Language Processing (NLP) in Healthcare by Types 2018-2023
Table Production Value Forecast of Natural Language Processing (NLP) in Healthcare by Types 2018-2023
Table Demand Volume of Natural Language Processing (NLP) in Healthcare by Downstream Industry 2013-2017
Table Demand Volume Forecast of Natural Language Processing (NLP) in Healthcare by Downstream Industry 2018-2023
Table Production Volume of Natural Language Processing (NLP) in Healthcare by Major Manufacturers 2013-2017
Table Production Value of Natural Language Processing (NLP) in Healthcare by Major Manufacturers 2013-2017
Table Headquarters Location and Established Time of Natural Language Processing (NLP) in Healthcare Major Manufacturer
Table Employees and Revenue Level of Natural Language Processing (NLP) in Healthcare Major Manufacturer
Table Representative Natural Language Processing (NLP) in Healthcare Product One of 3M
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of 3M
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of 3M 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of CERNER
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of CERNER
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of CERNER 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of IBM
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of IBM
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of IBM 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of MICROSOFT
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of MICROSOFT
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of MICROSOFT 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of NUANCE COMMUNICATIONS
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of NUANCE COMMUNICATIONS
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of NUANCE COMMUNICATIONS 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of HEATH FIDELITY
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of HEATH FIDELITY
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of HEATH FIDELITY 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of LINGUAMATICS
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of LINGUAMATICS
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of LINGUAMATICS 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of DOLBEY SYSTEMS
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of DOLBEY SYSTEMS
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of DOLBEY SYSTEMS 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of APIXIO
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of APIXIO
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of APIXIO 2013-2017
Table Representative Natural Language Processing (NLP) in Healthcare Product One of MMODAL IP
Table Representative Natural Language Processing (NLP) in Healthcare Product Two of MMODAL IP
Table Natural Language Processing (NLP) in Healthcare Sales, Revenue, Price and Gross Margin of MMODAL IP 2013-2017


RESEARCH METHODOLOGY

A research methodology is a systematic approach for assessing or conducting a market study. Researchers tend to draw on a variety of both qualitative and quantitative study methods, inclusive of investigations, survey, secondary data and market observation.

Such plans can focus on classifying the products offered by leading market players or simply use statistical models to interpret observations or test hypotheses. While some methods aim for a detailed description of the factors behind an observation, others present the context of the current market scenario.

Now let’s take a closer look at the research methods here.

Secondary Research Model

Extensive data is obtained and cumulated on a substantial basis during the inception phase of the research process. The data accumulated is consistently filtered through validation from the in-house database, paid sources as well reputable industry magazines. A robust research study requires an understanding of the overall value chain. Annual reports and financials of industry players are studied thoroughly to have a comprehensive idea of the market taxonomy.

Primary Insights

Post conglomeration of the data obtained through secondary research; a validation process is initiated to verify the numbers or figures. This process is usually performed by having a detailed discussion with the industry experts.

However, we do not restrict our primary interviews only to the industry leaders. Our team covers the entire value chain while verifying the data. A significant number of raw material suppliers, local manufacturers, distributors, and stakeholders are interviewed to make our findings authentic. The current trends which include the drivers, restraints, and opportunities are also derived through the primary research process.

Market Estimation

The market estimation is conducted by analyzing the data collected through both secondary and primary research. This process involves market breakdown, bottom-up and top- down approach.

Moreover, while forecasting the market a comprehensive statistical time series model is designed for each market. Macroeconomic indicators are considered to understand the current trends of the market. Each data point is verified by the process of data triangulation method to arrive at the final market estimates.

Final Presentation

The penultimate process results in a holistic research report. The study equips key industry players to undertake significant strategic decisions through the findings. The report encompasses detailed market information. Graphical representations of the current market trends are also made available in order to make the study highly comprehensible for the reader.

You can also purchase parts of this report. Do you want to check out a section wise price list?
Request for Special Pricing

Personalized Business Report Tailored to Your Requirements

  • Our expert analysts collaborate directly with you to comprehend your specific needs.
  • Get data on regions, segments, competitors, and vendors of your choice.
  • Information is presented in alignment with your exact preferences and formatting.
Request for customization
Report Snapshot
Free Sample Report

"Find new revenue generation opportunities"