International Journal on Science and Technology

E-ISSN: 2229-7677   •   Impact Factor: 9.88

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 16 Issue 2 April-June 2025 Submit your research before last 3 days of June to publish your research paper in the issue of April-June.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 16 Issue 2
2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Enhancing Healthcare Claim Processing with Generative AI: Leveraging AWS Bedrock and SageMaker for Efficiency and Accuracy

Author(s) Perumalsamy Ravindran
Country United States
Abstract Healthcare claims processing faces significant challenges in managing operational efficiency and cost-effectiveness while maintaining regulatory compliance. Integrating Generative AI technologies, specifically through AWS Bedrock and SageMaker platforms, offers transformative solutions for automating and optimizing claims processing workflows. Implementing these advanced technologies substantially improves processing speed, accuracy, and cost reduction across various healthcare organizations. Through intelligent document processing, anomaly detection, fraud prevention, and predictive adjudication capabilities, healthcare providers have significantly reduced administrative overhead while improving claims accuracy and processing efficiency. AI-driven solutions have enabled healthcare organizations to streamline operations, reduce manual intervention requirements, and enhance overall claims management effectiveness. These implementations have demonstrated marked improvements in provider satisfaction, reduced processing times, and increased operational efficiency while maintaining high accuracy standards and regulatory compliance.
Keywords Healthcare Claims Processing, Generative AI, AWS Bedrock, Machine Learning, Fraud Detection
Field Computer Applications
Published In Volume 16, Issue 1, January-March 2025
Published On 2025-03-28
Cite This Enhancing Healthcare Claim Processing with Generative AI: Leveraging AWS Bedrock and SageMaker for Efficiency and Accuracy - Perumalsamy Ravindran - IJSAT Volume 16, Issue 1, January-March 2025. DOI 10.71097/IJSAT.v16.i1.2961
DOI https://doi.org/10.71097/IJSAT.v16.i1.2961
Short DOI https://doi.org/g896d9
View / Download PDF File

Share this



CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJSAT DOI prefix is
10.71097/IJSAT

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 15 Isu 4Cover Page Vol 15 Isu 3Cover Page Vol 15 Isu 2

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJSAT
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us Message on WhatsApp +91-9687-182-185 editor@ijsat.org