Enhancing Patient Care with a Cloud-Driven Healthcare Chatbot on AWS

The increasing volume and complexity of healthcare information, coupled with the trend towards patient-centered care for quick access to health services re-quire new approaches to communication with patients. For the purpose of engaging the patients as well as providing support in real time, this project demonstrates healthcare Chabot system using AWS cloud environment. This paper enhances natural interaction with the users through the use of text data. The solution promises both scale and security as well as fast reaction rates due to Amazon Web Services such as Amazon Lex, DynamoDB, and AWS Lambda. These include the diagnosis of symptoms, booking of appointments. This approach has the advantages of simultaneously enhancing the security of patient’s data and rendering it more available. Thus, by following basic questions and first advising, the Chabot is planning to help reduce the pressure off the healthcare system, increasing patient’s satisfaction and further improving the service.

Authors

Institutions

Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1109/icaeca63854.2025.11012487
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhancing Patient Care with a Cloud-Driven Healthcare Chatbot on AWS

K Dinesh Kumar, Srinidhi Kannan, N Sumanth Reddy, P Mokshith et al.
AI in Service Interactions
article

Enhancing Patient Care with a Cloud-Driven Healthcare Chatbot on AWS

K Dinesh Kumar, Srinidhi Kannan, N Sumanth Reddy, P Mokshith, P Syam Prasad
article en

Abstract

The increasing volume and complexity of healthcare information, coupled with the trend towards patient-centered care for quick access to health services re-quire new approaches to communication with patients. For the purpose of engaging the patients as well as providing support in real time, this project demonstrates healthcare Chabot system using AWS cloud environment. This paper enhances natural interaction with the users through the use of text data. The solution promises both scale and security as well as fast reaction rates due to Amazon Web Services such as Amazon Lex, DynamoDB, and AWS Lambda. These include the diagnosis of symptoms, booking of appointments. This approach has the advantages of simultaneously enhancing the security of patient’s data and rendering it more available. Thus, by following basic questions and first advising, the Chabot is planning to help reduce the pressure off the healthcare system, increasing patient’s satisfaction and further improving the service.

Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 94%
AI in Service Interactions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.