Artificial Intelligence

NLP in Healthcare & Life Sciences Market worth $11.8 billion by 2028 – Exclusive Report by MarketsandMarkets™

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CHICAGO, Nov. 30, 2023 /PRNewswire/ — Improved clinical decision support, increased interoperability, real-time language translation, and patient-centric applications are the future of natural language processing (NLP) in healthcare. Key themes that highlight the necessity of responsible deployment and respect to regulatory norms include predictive analytics, ethical considerations, continuous learning, and growing use in telehealth. 

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™. NLP transforms healthcare by decoding text data, empowering efficient patient care. It aids healthcare staff in decision-making, medication management, and precise record-keeping by smartly analyzing medical information. NLP fosters evidence-based practices and encourages patient involvement in their healthcare journey. Its growth signifies improved treatments, streamlined workflows for healthcare professionals, and a more informed patient community. This symbiotic relationship between technology and healthcare promises a brighter, more accessible future in the medical landscape.
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346 – Tables64 – Figures360 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2018–2028
Base year considered
2022
Forecast period
2023–2028
Forecast units
USD Billion
Segments Covered
Offering, NLP Type, NLP Technique, Application, End Users, and Region
Geographies covered
North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
Companies covered
IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle Corporation (US), Inovalon(US), Dolbey and Company (US), Averbis (Germany), SAS Institute (US), 3M (US), Press Ganey (US), Ellipsis Health (US), Centene Corporation (US), Lexalytics (US), Caption Health (US), Clinithink (US), Hewlett Packard Enterprise (US), Oncora Medical (US), Flatiron Health (US), Apixio (US), Edifecs (US), John Snow Labs (US), ITRex Group (US),  Forsee Medical (US), Gnani.ai (India), Notable (US), Biofourmis (US), Suki (US), Wave Health Technologies (US), Corti (Denmark), CloudMedx (US), MedlnReal (Netherlands), Emtelligent (Canada), Enlitic (US), and Deep 6 AI (US)
Text Classification to hold the largest market size during the forecast period.
Text classification in NLP in Healthcare & Life Sciences Market categorizes medical data, organizing it into meaningful groups such as diagnoses, symptoms, or treatments. This systematic sorting enables swift data analysis, aiding in decision-making processes for healthcare professionals. It automates administrative tasks, swiftly flags critical information, and uncovers patterns crucial for predictive analytics and research insights. By efficiently structuring information, text classification optimizes workflows, enhances clinical decision support systems, and accelerates research efforts. This streamlined approach expedites diagnoses, treatments, and discoveries, serving as a catalyst for improved patient care and advancements in healthcare practices.
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Solutions Segment to account for the largest market share during the forecast period.
NLP solutions in Healthcare & Life sciences revolutionize data management, diagnosis, and patient interaction. These solutions streamline clinical documentation, extracting insights from unstructured data such as patient records and medical literature. It aids in precision medicine by analyzing genetic data and identifying tailored treatments. NLP powers chatbots and virtual assistants, improving patient engagement and support. Additionally, it accelerates drug discovery processes by mining vast scientific literature for patterns and insights. Ethical considerations, including privacy and bias, remain focal points in deploying NLP solutions, ensuring responsible and effective integration into these critical sectors.
Asia Pacific to exhibit the highest CAGR during the forecast period.
The CAGR of Asia Pacific is estimated to be highest during the forecast period. The advanced and dynamic adoption of new technologies has made Asia Pacific the fastest-growing economic region. The healthcare industry in this region has gained momentum with increased AI and ML spending. Governments across this region are taking various initiatives to implement AI in businesses. The region is hence expected to witness a noticeable growth in the adoption of NLP technologies, enabling healthcare providers to automate administrative workflows, invest more time in inpatient care, and improve the patient experience using real-time data. By applying NLP technologies, healthcare organizations optimize the manual review of unstructured text within medical records to uncover clinical insights.
Top Key Companies in NLP in Healthcare & Life Sciences Market:
Major vendors in the global NLP in Healthcare & Life Sciences Market are IBM (US), Microsoft (US), Google (US), AWS (US), IQVIA (US), Oracle Corporation (US), Inovalon(US), Dolbey and Company (US), Averbis (Germany), SAS Institute (US), 3M (US), Press Ganey (US), Ellipsis Health (US), Centene Corporation (US), Lexalytics (US), Caption Health (US), Clinithink (US), Hewlett Packard Enterprise (US), Oncora Medical (US), Flatiron Health (US), Apixio (US), Edifecs (US), John Snow Labs (US), ITRex Group (US),  Forsee Medical (US), Gnani.ai (India), Notable (US), Biofourmis (US), Suki (US), Wave Health Technologies (US), Corti (Denmark), CloudMedx (US), MedlnReal (Netherlands), Emtelligent (Canada), Enlitic (US), and Deep 6 AI (US).
Recent Developments:
In October 2023, Inovalon collaborated with AWS to develop AI/ML solutions for the healthcare industry. The initial focus will be on risk adjustment, but the collaboration is expected to expand to other areas, such as disease management, population health, and clinical decision support. The goal of the collaboration is to improve patient outcomes and reduce costs.In September 2023, Apollo Hospitals announced an extended partnership with Google Cloud to make healthcare accessible to every Indian through its digital platform, Apollo 24|7. The partnership involved the development of a Clinical Intelligence Engine (CIE) using Google Cloud’s Vertex AI and generative AI models. Apollo Hospitals is also considering the use of Med-PaLM 2, a Google-developed LLM capable of responding to medical queries and generating clinical text summaries, further enhancing healthcare services.In August 2023, Oracle partnered with TeleVox to provide cloud-based patient engagement solutions to healthcare organizations. This partnership would combine TeleVox’s expertise in patient engagement with Oracle Cloud Infrastructure’s (OCI) scalability, security, and reliability.In April 2023, Moderna signed an agreement with IBM to harness quantum computing and artificial intelligence for mRNA research, with the goal of accelerating scientific advancements in mRNA therapeutics and vaccines. This agreement aims to explore cutting-edge technologies to potentially revolutionize healthcare and biotechnology by leveraging data-driven insights and innovative solutions.In March 2023, Syneos Health announced a multi-year partnership with Microsoft to use its platform for deploying artificial intelligence (AI) in its clinical trials and commercial programs.Inquire Before Buying@ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=131821021
NLP in Healthcare & Life Sciences Market Advantages:
Efficiency: By automatically extracting pertinent information from unstructured clinical notes, natural language processing (NLP) can expedite the clinical recording process and save time and effort when manually entering data.Accuracy: Automated documentation promotes more thorough and accurate patient records by reducing errors.Analysing large volumes of clinical data, natural language processing (NLP) can offer healthcare practitioners insightful information that reinforces evidence-based decision-making.Alerts and Notifications: Natural Language Processing (NLP) systems has the ability to produce alerts and notifications that inform healthcare practitioners about possible problems, like missing diagnostic criteria or drug interactions.Chatbots and virtual assistants: Equipped with natural language processing (NLP), these AI tools may converse with patients, respond to their questions, and offer guidance, all of which contribute to a better patient experience.Language Understanding: Natural language processing (NLP) enables systems to comprehend and react to natural language inquiries, facilitating patient-provider communication and the retrieval of pertinent information.Risk assessment: By analysing patient data to find trends and gauge a patient’s chance of contracting a particular illness, natural language processing (NLP) algorithms make it possible to take preventative measures.Early Detection: Natural Language Processing (NLP) can help identify diseases early on and may even enhance the effectiveness of treatment by analysing vast amounts of data.Report Objectives
To define, describe, and predict the NLP in the Healthcare & Life sciences market by offering (solutions and services), NLP type, application, NLP technique, end users, and regionTo provide detailed information about major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growthTo analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leadersTo forecast the market size of segments with respect to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin AmericaTo profile key players and comprehensively analyze their market rankings and core competenciesTo analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the NLP in the Healthcare & Life sciences marketBrowse Adjacent Markets: Artificial Intelligence (AI) Market Research Reports & Consulting
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