From Idea to Publication: A Step-by-Step Guide to Original Research in Radiology with AI-Integrated Workflow.

Authors

Isabela Hernandez, Daniel Souza, Cinthia Del Toro, Kristin Parker, Adriana Falcon Vazquez, Gary H Danton, Ty Subhawong, Francesco Alessandrino

Published in

Academic radiology. Oct 07, 2026. Epub Oct 07, 2026.

Abstract

Over the past decade, according to the National Resident Matching Program Charting Outcomes data, scholarly output of matched United States Medical Doctor radiology applicants has more than doubled, with applicants reporting an average of 12.0 published scholarly works in 2024 compared to 5.7 in 2014. Despite this shift, structured guidance on how to produce peer-reviewed scholarly work remains limited for radiology trainees, and most existing guides predate the widespread availability of artificial intelligence (AI) tools.
This guide provides a five-step framework, covering choosing a topic of interest, methodology development, presentation of results, manuscript writing, and revision and submission, with explicit integration of AI tools at each stage.
A framework for responsible AI use and disclosure is provided.
Scientific writing is a teachable skill. AI tools, when used with transparency and integrity, lower the threshold for entry for radiology trainees and should be integrated into scientific writing education. This guide provides a reproducible, AI-integrated framework applicable to trainees at any stage of training and seeking to publish peer-reviewed scholarly works.

PMID:
42844067
Bibliographic data and abstract were imported from PubMed on 08 Oct 2026.

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