Personalized Care Through Sentiment Analysis and Natural Language Processing
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In hospitals and other healthcare organizations, understanding patient feedback helps to exceed in providing top-notch care. Sentiment analysis to enhance patient care is the way to know how patients feel about different service aspects, including processes, infrastructure, treatment, and healthcare professionals. Enhancing healthcare with sentiment analysis means removing human bias through consistent analysis, gaining real-time insights about patient satisfaction, and improving standards of care by incorporating patient feedback. In this paper, we will examine several facets of utilizing sentiment analysis for patient happiness, such as the various forms of sentiment analysis, its applications in healthcare, and its precise methodology. This work intends to guide algorithm selection and progress NLP research by adding to the continuing conversation on advancing sentiment analysis in the context of big data and computational linguistics. These results highlight the adaptability of NLP methods and their potential to enhance patient outcomes, research, and healthcare delivery.
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