International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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

Call for Paper Volume 6 Issue 6 November-December 2024 Submit your research before last 3 days of December to publish your research paper in the issue of November-December.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 6 Issue 6
November-December 2024

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

Ai Radiologist: Vit & Bert Power Chest X-ray Report Automation

Author(s) Mr.Balamurugan V, Mr.Giriprasath K S
Country India
Abstract Radiology workloads soar, straining radiologists and potentially delaying diagnoses. We introduce the "AI Radiologist," a novel approach leveraging ViT (Vision Transformer) and BERT (Bidirectional Encoder Representations from Transformers) to automate chest X-ray report generation. The AI Radiologist employs a multi-stage pipeline. ViT extracts rich visual features from preprocessed X-rays, capturing spatial relationships and subtle details. These features are then fed into a BERT model, trained on a massive dataset of chest X-ray reports and corresponding images. BERT analyzes these features and generates comprehensive, natural language reports, including findings, diagnoses, and recommendations. This AI-powered approach offers compelling advantages. Compared to traditional methods, the AI Radiologist boasts improved accuracy and efficiency, potentially alleviating radiologist burnout and freeing them for complex cases.
Moreover, generated audio descriptions can enhance accessibility for visually impaired individuals. We evaluate the AI Radiologist extensively, demonstrating its superior performance against existing benchmarks. Our results suggest this technology has the potential to revolutionize chest X-ray reporting, promoting faster diagnoses, improved patient care, and a more efficient healthcare system.
Keywords AI, Radiology, Chest X-ray, ViT, BERT, Report Automation, Medical Imaging
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-06
Cite This Ai Radiologist: Vit & Bert Power Chest X-ray Report Automation - Mr.Balamurugan V, Mr.Giriprasath K S - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.16028
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.16028
Short DOI https://doi.org/gtp8m7
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

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

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 6 Isu 6Cover Page Vol 6 Isu 5Cover Page Vol 6 Isu 4

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 IJFMR
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 +91-9898-5948-55 editor@ijfmr.com