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@article{176836,
author = {KABILAN M and DHANRAJ P and KANDUKURU LOHITH REDDY and KASTHURI M},
title = {smart diagnosis and patient care using NLP},
journal = {International Journal of Innovative Research in Technology},
year = {2025},
volume = {11},
number = {11},
pages = {6142-6146},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=176836},
abstract = {The rapid advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) are revolutionizing healthcare, enabling more efficient and accessible patient care. This research explores the development of an AI-powered healthcare system that leverages NLP to analyze patient symptoms and provide preliminary diagnoses. Unlike traditional chatbot systems, which rely on predefined keyword-based responses, this solution integrates advanced machine learning models to understand patient queries in a contextual manner and offer accurate, domain-specific insights.
The system enhances patient care by incorporating automated diagnosis, appointment scheduling, medication reminders, and access to essential health information, reducing unnecessary hospital visits and optimizing healthcare accessibility. By utilizing decision tree algorithms and NLP-driven text analysis, it ensures quick and reliable symptom evaluation, empowering users with timely health recommendations. Additionally, cloud-based storage and synchronization mechanisms enable seamless data access and real-time updates, improving efficiency in remote healthcare services.
This research highlights how AI-driven smart diagnosis can support both healthcare professionals and patients by providing cost-effective, scalable, and on-demand assistance. Future enhancements may include specialized medical features, multilingual support, and deeper integration with IoT-enabled medical devices, further transforming digital healthcare solutions.},
keywords = {Artificial Intelligence, Natural Language Processing, Healthcare Chatbot, Symptom Analysis, Remote Patient Care, Cloud Computing.},
month = {April},
}
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