Abstract
This manuscript presents a methodical examination of the utilization of Artificial Intelligence (AI) in the assessment of emotions in texts related to healthcare, with a particular focus on the incorporation of Natural Language Processing (NLP) and deep learning technologies. We scrutinize numerous research studies that employ AI to augment sentiment analysis, categorize emotions, and forecast patient outcomes based on textual information derived from clinical narratives, patient feedback on medications, and online health discussions. The review demonstrates noteworthy progress in the precision of algorithms used for sentiment classification, the prognostic capabilities of AI models for neurodegenerative diseases, and the creation of AI-powered systems that offer support in clinical decision-making.
Citation
@inproceedings{nag2023EmotionalIntelligenceArtificial,
address = {Raipur, India},
title = {Emotional {Intelligence} {Through} {Artificial} {Intelligence}: {NLP} and {Deep} {Learning} in the {Analysis} of {Healthcare} {Texts}},
isbn = {979-8-3503-3091-5},
shorttitle = {Emotional {Intelligence} {Through} {Artificial} {Intelligence}},
url = {https://ieeexplore.ieee.org/document/10489117/},
doi = {10.1109/ICAIIHI57871.2023.10489117},
booktitle = {2023 {International} {Conference} on {Artificial} {Intelligence} for {Innovations} in {Healthcare} {Industries} ({ICAIIHI})},
publisher = {IEEE},
author = {Nag, Prashant Kumar and Bhagat, Amit and Vishnu Priya, R. and Khare, Deepak Kumar},
month = dec,
year = {2023},
pages = {1--7}
}