Evidence map›Paper›PMID 41473390›Full record

ArticleTechnical innovations & patient support in radiation oncology2025

AI based sentiment analysis of online discussions related to cervical brachytherapy.

R Kouzy, M K Rooney, E E Cha, S Vinjamuri, H Wu, Z El Kouzi, O Mohamad, T T Sims, C R Weil, N Taku and 6 more

Abstract read
In one paragraph

Article in Technical innovations & patient support in radiation oncology, 2025. 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

16 authors.

R KouzyDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
M K RooneyDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
E E ChaDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
S VinjamuriGandhi Medical College, Secunderabad, India.
H WuDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Z El KouziDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
O MohamadDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
T T SimsDepartment of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
C R WeilDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
N TakuDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
L L LinDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
A JhingranDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
P EifelDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
M JoynerDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
L E ColbertDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
A H KloppDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose/Objectives: Few studies have documented the experiences of patients receiving cervical brachytherapy. While evidence regarding quality of life issues in this population has emerged, traditional structured questionnaires often fail to capture the full range of patient perspectives. We hypothesized that analyzing unfiltered patient discussions from online forums would reveal unique insights into patient experiences, including previously unidentified emotional responses, concerns, and coping strategies. This study applied an artificial intelligence (AI) workflow to analyze cervical cancer and brachytherapy discussions from an online forum. Materials/Methods: We extracted posts and comments from the subreddit r/cervicalcancer, focusing on discussions about brachytherapy between November 2020 and January 2024. We applied a processing pipeline to prepare the data for analysis. The content was analyzed using RoBERTa, a pre-trained deep learning model, to categorize sentiments as positive, negative, or neutral. We further evaluated posts using pre-defined keyword tagging to identify dominant topics within conversations based on recent literature. Results: The analysis encompassed 898 unique posts and comments from an initial dataset of 1075 entries. Overall sentiments were categorized as 40.4% positive, 29.9% negative, and 29.7% neutral. Discussions related to "Bowel Domain" showed the highest proportion of negative sentiments (51.2%) among all topics. "Urinary Domain" (46.8%), "Pain" (43.4%), "Fatigue" (42.4%), and "Anesthesia" (41.4%) discussions also reflected predominantly negative sentiments. In contrast, "Recovery" and "Survivorship" discussions were predominantly positive. The sentiments on "Sex" and "Mental Health" related topics displayed a more balanced distribution between positive and negative perspectives. Conclusion: Our study demonstrates the value of analyzing unstructured patient narratives from online forums related to cervical brachytherapy. We identified patterns of concerns that can inform clinical practice, particularly regarding patient education about bowel and urinary side effects. These findings can improve informed consent discussions and help clinicians better address patients' significant concerns. Further work will focus on developing automated systems to bridge the gap between clinicians' understanding and patients' lived experiences.

Indexed as

Artificial IntelligenceBrachytherapyCervical CancerNatural Language Processing

Identifiers

PMID41473390
PMCPMC12746271

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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.