Table 11.

Comparative assessment of limitations and future perspectives for research in report generation.

References	Specific limitation	Specific future perspective
Zhong et al (2023)	Focus only on chinese radiology reports; limited to ct and mri reports; inferior performance in certain report types; challenges in causal reasoning report generation; generalizability concerns in global contexts	Investigate performance with more diverse data; expand to other image modalities; improve performance in complex reports; enhance causal reasoning in reports; test and adapt in varied healthcare systems
Yan and Pei (2022)	MeSH word prediction accuracy	Incorporate organ localization; expand downstream tasks
Leonardi et al (2023)	Scarcity of data; localization errors; computational resource limitations; usability validation issues	Explore data augmentation techniques; improve localization accuracy; develop resource-efficient models; conduct usability assessments
Li (2023)	Limited data availability; model comparison constraints; caption diversity issues	Develop effective data augmentation methods; explore various advanced language models; enhance caption diversity and control
Tanida et al (2023)	Strong supervision reliance; focus on isolated chest x-rays; incomplete coverage of reference reports	Adapt for limited supervision; utilize sequential exam information; create hybrid systems for comprehensive sentence generation
Kong et al (2022)	Limited focus on abnormality term generation	Apply semantic features to a conditional linguistic decoder for enhanced sentence generation