Summary of Emotional Intelligence Through Artificial Intelligence : Nlp and Deep Learning in the Analysis Of Healthcare Texts, by Prashant Kumar Nag et al.
Emotional Intelligence Through Artificial Intelligence : NLP and Deep Learning in the Analysis of Healthcare Texts
by Prashant Kumar Nag, Amit Bhagat, R. Vishnu Priya, Deepak kumar Khare
First submitted to arxiv on: 14 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The manuscript presents an examination of Artificial Intelligence (AI) used in assessing emotions in healthcare-related texts, focusing on Natural Language Processing (NLP) and deep learning technologies. It reviews research studies employing AI to augment sentiment analysis, categorize emotions, and forecast patient outcomes from clinical narratives, patient feedback, and online health discussions. The review shows progress in algorithm precision for sentiment classification, prognostic capabilities for neurodegenerative diseases, and AI-powered systems supporting clinical decision-making. AI applications have enhanced personalized therapy plans by integrating patient sentiment, contributing to early mental health disorder identification. Challenges persist, including ethical AI application, patient confidentiality, and addressing algorithm biases. However, AI’s potential to revolutionize healthcare is evident, offering a future where healthcare is more knowledgeable, efficient, and empathetic. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Artificial Intelligence (AI) is being used to understand emotions in healthcare texts! This paper looks at how AI can help analyze emotions in things like doctor notes, patient feedback, and online health discussions. Researchers are using AI to get better at understanding how people feel about their treatment, which could lead to more personalized care. They’re also looking at how AI can predict patient outcomes and help doctors make decisions. While there are some challenges with using AI in healthcare, like making sure it’s used fairly and patients’ information is kept safe, the possibilities are exciting! With AI, healthcare could become more efficient, accurate, and even more compassionate. |
Keywords
» Artificial intelligence » Classification » Deep learning » Natural language processing » Nlp » Precision
