Abstract
The healthcare sector enhances the integration of artificial intelligence, natural language processing and machine learning in data governance for developing automation procedures. Data management offered AI-powered ETL testing with the adoption of an automation framework for resolving data governance issues . This insight promotes operational efficiency with assurance of data quality that empowers data security by ML, AI and NLP frameworks. The framework allows healthcare institutions to arrange unstructured data in effective insights into patient care and treatment procedures. Advanced analytics leads to the development of predictions on patient outcomes in treatment procedures. The automated process of ETL improves efficient information collection by NPL with the creation of predictive models in monitoring data management by ML
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal For Multidisciplinary Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.