NLP in Healthcare & Life Sciences Market worth $11.8 billion by 2028, growing at a CAGR of 34.4%: Report by MarketsandMarkets™

Chicago, Jan. 09, 2024 (GLOBE NEWSWIRE) -- The global NLP in Healthcare & Life Sciences Market is projected to grow from USD 2.7 billion in 2023 to USD 11.8 billion by 2028, at a CAGR of 34.4% during the forecast period, according to a new report by MarketsandMarkets™.  The natural language processing holds significant promise in Healthcare & Life sciences by efficiently handling vast amounts of unstructured medical data. This encompasses various sources such as doctor notes, medical records, clinical trial reports, and patient-generated service reviews on social media. Research shows, that around 80% of healthcare data remains unstructured, limiting its potential utilization. NLP steps in to address this by analyzing and extracting insights from this data. By doing so, it empowers healthcare professionals, offering valuable guidance that informs more informed decision-making for doctors and pharmacists, ultimately leading to improved patient care and outcomes.

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NLP in Healthcare & Life Sciences Market Dynamics:


  1. Rising demand to enhance care delivery and patient engagement
  2. Need for predictive analytics to improve significant health concerns
  3. Focus on enhancing clinical decision support


  1. Issues related to domain-specific language and medical terminology in NLP model development
  2. Complexity in integrating NLP with established healthcare system


  1. Rising adoption of computer-assisted coding to enhance productivity
  2. Emergence of advanced AI technology for generating valuable insights for healthcare
  3. Emergence of cognitive computing for medicine applications

List of Key Players in NLP in Healthcare & Life Sciences Market:

  • IBM (US)
  • Microsoft (US)
  • Google (US)
  • AWS (US)
  • IQVIA (US)
  • Oracle Corporation (US)
  • Inovalon(US)
  • Dolbey and Company (US)
  • Averbis (Germany)
  • SAS Institute (US)

The NLP in Healthcare & Life Sciences Market, by offering, is segmented into solutions, and services. Further, the solution segment is divided into by type, and by deployment mode. By type, solutions segment is further bifurcated into software and platforms. Based on deployment mode the market is further bifurcated into on-premise and cloud. The services segment is categorized into professional and managed services. Professional services include training & consulting, system integration & implementation, and support & maintenance services.

Based on NLP type, the NLP in Healthcare & Life Sciences Market is bifurcated into rule-based, statistical, neural, and hybrid. Rule-based NLP relies on predefined guidelines and linguistic rules to interpret data, useful for standardizing terminology or simple tasks. Statistical NLP utilizes probability models, aiding in sentiment analysis or information extraction. Neural NLP, powered by deep learning, excels in complex tasks such as language translation and sentiment analysis, leveraging neural networks to comprehend context and nuances within medical texts. Hybrid NLP amalgamates these approaches, merging rule-based precision with the adaptive learning of neural networks for enhanced accuracy in clinical decision-making, entity recognition, or summarization.

Based on NLP technique, the market is segmented into optical character recognition, name entity recognition, sentiment analysis, text classification, topic modeling, image & pattern recognition, and other NLP techniques (predictive risk analytics, auto coding, spelling correction, email filtration, question answering, and simulation & modeling).

Based on application, the market is segmented into clinical decision & diagnosis, drug discovery & development, clinical trial matching, electronic health record search & retrieval, healthcare chatbots & virtual assistants, clinical documentation processing, medical imaging, and other applications (telemedicine & telehealth consultation, and healthcare knowledge graphs).

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Based on end users, the NLP in Healthcare & Life Sciences Market is segmented into clinical practitioners, healthcare researchers, healthcare administrators, health insurance & payer professionals, pharmaceutical & biotech companies, and other end users (medical educators & researchers, data privacy & ethics consultants). These end users leverage NLP for enhanced diagnostics, personalized treatments, streamlined data analysis, and improved patient interactions, optimizing overall healthcare services and outcomes.

The NLP in Healthcare & Life Sciences Market has been segmented into five regions: North America, Europe, Asia Pacific, Middle East and Africa, and Latin America. North America has been a pioneer in adopting NLP in Healthcare & Life Sciences, driven by its technological advancement.  In North America, NLP's integration within healthcare and life sciences is swiftly gaining traction. This adoption is reshaping medical practices by enabling precision medicine, refining data analysis methodologies, and fostering advancements in patient care. Its implementation signifies a paradigm shift towards more personalized treatments, streamlined data-driven insights, and ultimately, an improved landscape for healthcare delivery and patient outcomes across the region. Also, The growth of NLP in Healthcare & Life sciences across Asia Pacific stems from data abundance, diverse languages, aiding research and efficiency, supported by government investment, tech innovation, and its pivotal role during the COVID-19 pandemic.

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