Emotional Intelligence Through Artificial Intelligence : NLP and Deep
  Learning in the Analysis of Healthcare Texts
Prashant Kumar Nag Amit Bhagat R. Vishnu Priya Deepak kumar Khare
This manuscript presents a methodical examination of the utilization of
Artificial Intelligence in the assessment of emotions in texts related to
healthcare, with a particular focus on the incorporation of Natural Language
Processing 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. Remarkably, the utilization of AI
applications has exhibited an enhancement in personalized therapy plans by
integrating patient sentiment and contributing to the early identification of
mental health disorders. There persist challenges, which encompass ensuring the
ethical application of AI, safeguarding patient confidentiality, and addressing
potential biases in algorithmic procedures. Nevertheless, the potential of AI
to revolutionize healthcare practices is unmistakable, offering a future where
healthcare is not only more knowledgeable and efficient but also more
empathetic and centered around the needs of patients. This investigation
underscores the transformative influence of AI on healthcare, delivering a
comprehensive comprehension of its role in examining emotional content in
healthcare texts and highlighting the trajectory towards a more compassionate
approach to patient care. The findings advocate for a harmonious synergy
between AI's analytical capabilities and the human aspects of healthcare.