MarketsandMarkets forecasts the global Natural Language Processing (NLP) in Healthcare and Life Sciences Market size to grow from USD 1.5 billion in 2020 to USD 3.7 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 20.5% during the forecast period. The major growth factors of the NLP in healthcare and life sciences market include the growing demand for improving Electronic Health record (EHR) data usability to enhance patient care, and ability to analyze and extract meaning from narrative texts and non-related data sources.
Large enterprises segment to hold a larger market size during the forecast period
The NLP in healthcare and life sciences market by organization size is segmented into large enterprises and Small and Medium-sized Enterprises (SMEs). The large enterprises segment is expected to have a larger market size during the forecast period, due to the access of large enterprises to the large volume of data being generated from various sources that demand for real-time data insights. However, the SMEs segment is expected to grow at a higher CAGR during the forecast period. SMEs are growing at a rapid rate and are keen to implement NLP on the cloud that will help them analyze huge volumes of data and make faster decisions for offering optimum patient care.
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By end user, the NLP for researchers segment to grow at the highest CAGR during the forecast period
The NLP in healthcare and life sciences market by end user is segmented into four categories: NLP for physicians, NLP for researchers, NLP for patients, and NLP for clinical operators. The NLP for researchers segment is expected to grow at the highest CAGR during the forecast period. The NLP for researchers segment is the most affected by Artificial Intelligence (AI) trends and possibilities due to the nature and amount of data that is produced by healthcare companies. Researchers are increasingly adopting NLP solutions for qualitative research purposes. The development of NLP-enabled qualitative methods could therefore provide clinical investigators new tools for exploring research questions that may not have been pursued otherwise. Medical researchers are using NLP and Machine Learning (ML) to improve care coordination by analyzing large sets of unstructured health data and drawing actionable insights from them.
The major NLP in healthcare and life sciences vendors include 3M (US), Cerner (US), Nuance (US), Health Fidelity (US), Dolbey (US), Microsoft (US), IBM (US), Google (US), AWS (US), Apixio (US), Averbis (Germany), Linguamatics (UK), Clinithink (Georgia), Wave Health Technologies (Georgia), Inovalon (US), and Lexalytics (US). These players have adopted various growth strategies, such as partnerships, agreements, and collaborations; and new product launches, to further expand their presence in the global NLP in healthcare and life sciences market. Partnerships, new product launches, acquisitions, and product enhancements have been the dominating strategies adopted by the major players from 2018 to 2020, which has helped them innovate their offerings and broaden their customer base.
Cerner (US) is a leading supplier of Health Care Information Technology (HCIT) solutions and tech-enabled services. It further offers solutions and services that support the clinical, financial, and operational needs of organizations of all sizes. Cerner has its systems present in more than 27,500 facilities worldwide, including hospitals, physician practices, laboratories, ambulatory centers, behavioral health centers, cardiac facilities, radiology clinics, surgery centers, extended care facilities, retail pharmacies, and employer sites. Cerner and Amazon partnered to offer Artificial Intelligence (AI) and Machine Learning (ML) tools in the healthcare vertical. The ML offerings of Amazon Web Services (AWS) further include voice recognition and NLP to help Cerner strengthen its roadmap. Back in 2011, Cerner acquired Clairvia, which provides solutions for various companies that use EHRs. Cerner offers practical applications based on AI and NLP in the healthcare and life sciences market. It further offers solutions on the unified Cerner Millennium architecture and on the HealtheIntent cloud-based platform. Cerner’s NLP solution allows providers to mine EMR data for patient summaries, coding reconciliation, and regulatory use cases.
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Nuance (US) provides speech recognition and AI in the healthcare segment thus transforming patient care with the help of AI-powered solutions for physicians, radiologists, and hospitals. It provides omni-channel solutions that help drive conversation with customers. It also provides security with the help of innovative biometric solutions and boosts productivity with the help of speech recognition solutions that act amazingly faster thus saving time and excess cost. It caters to companies across several industries, including healthcare, financial, telecom, and the government. The company further focuses on linguistic technologies, AI and reasoning, conversational systems, applied NLP, clinical language understanding in the healthcare vertical. Nuance’s Natural Language Understanding (NLU) provides a platform for self service solutions by understanding customers using conversational IVR and virtual assistant solutions.
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