According to a research report “NLP in Healthcare & Life Sciences Market by Offering, NLP Type (Statistical, Neural), NLP Technique (Sentiment Analysis, Topic Modeling), Application (Clinical Trial Matching, Clinical Decision Support), End User and Region – Global Forecast to 2028″ published by MarketsandMarkets, the global market for 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. 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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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.
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.
Key Player
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).
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