{"id":72869,"date":"2024-04-17T09:54:15","date_gmt":"2024-04-17T07:54:15","guid":{"rendered":"https:\/\/intellias.com\/?post_type=blog&p=72869"},"modified":"2024-07-01T17:44:44","modified_gmt":"2024-07-01T15:44:44","slug":"natural-language-processing-nlp-in-healthcare","status":"publish","type":"blog","link":"https:\/\/intellias.com\/natural-language-processing-nlp-in-healthcare\/","title":{"rendered":"Leveraging Natural Language Processing (NLP) in Healthcare"},"content":{"rendered":"
An increasing number of technology companies, ranging from startups to tech giants, aim to redesign healthcare using artificial intelligence. Some come and go unnoticed; others have shaken the sector. As AI proves its effectiveness in healthcare, particularly in enhancing diagnostic accuracy, the industry keeps seeking the best ways to harness AI to provide safety, accessibility, and equitable care for all patients. The initial areas of AI impact in healthcare include administration, medical imaging<\/a>, and drug development.<\/p>\n As reactive as the healthcare sector can be, employing natural language processing (NLP) across the industry has already become a necessity rather than an emerging trend. Advanced systems combining NLP with machine learning algorithms unravel the complexities of human language, enabling efficient data processing and making NLP a go-to tool for everyone from overworked clinicians to care and insurance providers as well as ROI-focused medical sales and marketing teams.<\/p>\n The increase in the number of institutions that use NLP in healthcare comes from the global push for digital transformation and data-driven processes, sparking the rise of smart ecosystems.<\/p>\n