Automatic Medical Report Generation: Methods and Applications

The increasing demand for medical imaging has surpassed the capacity of available radiologists, leading to diagnostic delays and potential misdiagnoses. Artificial intelligence (AI) techniques, particularly in automatic medical report generation (AMRG), offer a promising solution to this dilemma. This review comprehensively examines AMRG methods from 2021 to 2024. It (i) presents solutions to primary challenges in this field, (ii) explores AMRG applications across various imaging modalities, (iii) introduces publicly available datasets, (iv) outlines evaluation metrics, (v) identifies techniques that significantly enhance model performance, and (vi) discusses unresolved issues and potential future research directions. This paper aims to provide a comprehensive understanding of the existing literature and inspire valuable future research.

Authors

Institutions

Publication Details

Journal
APSIPA Transactions on Signal and Information Processing
Published
2024-10-17
DOI
https://doi.org/10.1561/116.20240044
Citations
10
Primary Topic
Advanced Text Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.47
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Automatic Medical Report Generation: Methods and Applications

Rabab Ward, Z. Jane Wang, Guo Li, Anas M. Tahir et al.
10 citations
APSIPA Transactions on Signal and Information Processing
Advanced Text Analysis Techniques
3.47
article

Automatic Medical Report Generation: Methods and Applications

Rabab Ward, Z. Jane Wang, Guo Li, Anas M. Tahir, Dong Zhang
article en
10 citations

Abstract

The increasing demand for medical imaging has surpassed the capacity of available radiologists, leading to diagnostic delays and potential misdiagnoses. Artificial intelligence (AI) techniques, particularly in automatic medical report generation (AMRG), offer a promising solution to this dilemma. This review comprehensively examines AMRG methods from 2021 to 2024. It (i) presents solutions to primary challenges in this field, (ii) explores AMRG applications across various imaging modalities, (iii) introduces publicly available datasets, (iv) outlines evaluation metrics, (v) identifies techniques that significantly enhance model performance, and (vi) discusses unresolved issues and potential future research directions. This paper aims to provide a comprehensive understanding of the existing literature and inspire valuable future research.

APSIPA Transactions on Signal and Information ProcessingVol. 13(1)
University of British Columbia (CA)
Openalex Percentile: Top 6%
Advanced Text Analysis Techniques
3.47
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.