Evidence map›Paper›PMID 42369824›Full record

ArticleJAMIA open2026

Improving readability of layperson abstracts and summaries in oncology using task-specific large language model powered tool: results from the BRIDGE-AI 7 study.

Aalamnoor S Pannu, Ilicia Cano, Ethan Layne, Gus Miranda, Jie Cai, Conner Ganjavi, Vasileios Magoulianitis, Karanvir Gill, Gerhard Fuchs, Mihir Desai and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JAMIA open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Aalamnoor S PannuUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.ORCID https://orcid.org/0009-0004-7320-655X
Ilicia CanoUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Ethan LayneUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Gus MirandaUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Jie CaiUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Conner GanjaviUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Vasileios MagoulianitisUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Karanvir GillUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Gerhard FuchsUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Mihir DesaiUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Inderbir GillUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Giovanni E CacciamaniUSC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To compare the performance of task-specific generative AI, with general-purpose large language models (LLMs) in generating more readable lay abstracts and summaries (LASs) of Oncology research. Materials and Methods: Twenty-five randomly selected abstracts from the top 5 journals in Oncology were processed into LASs using a task specific LLM-powered tool (Pub2Post) and 5 general-purpose LLMs (ChatGPT-5, Claude, Gemini, DeepSeek and Grok). Two prompting strategies (Specific and Generic) were applied. Consistency was tested across 3 outputs, producing a total of 825 LASs. Readability-scores and text-metrics were calculated. The "best test" per model was selected based on lowest SMOG Index, which was subsequently used to compare the 6 GAI platforms. Comparisons were performed using Kruskal-Wallis tests, with significance set at Results: All the platforms demonstrated consistent intra-model outputs across triplicate generations (all Discussion and Conclusion: Task-specific GAI powered tools (Pub2Post) generated consistently more readable LASs compared to 5 commercially available LLMs, regardless of prompting strategy. These findings highlight the value of purpose-built GAI tools for enhancing public understanding and accessibility of oncology research, with implications for improving patient-education.

Indexed as

artificial intelligencegenerative AIGPTGPT-5large language modelslay summaryPub2Postreadability

Identifiers

PMID42369824
PMCPMC13296995

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.