ArticleOpen journal of obstetrics and gynecology2024
Digital Twin of the Female Pelvic Floor.
Article in Open journal of obstetrics and gynecology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Bladder Digital Twins for Neuromodulation: Current Platforms and a Roadmap to Closed-Loop Therapy.International neurourology journal · 2026Article
- Toward a Digital Twin of the Female Pelvic Floor.EC gynaecology · 2025Article
- Innovative design and modelling to improve sex and gender analysis in clinical trials.BMJ (Clinical research ed.) · 2025Article
- Innovations in Stress Urinary Incontinence: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Toward demographic robustness in digital patient twins: Addressing the gender data gap.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Digital twin technology, originally developed for intricate physical systems, holds great potential in women's healthcare, particularly in the management of pelvic floor disorders. This paper delves into the development of a digital twin specifically for the female pelvic floor, which can amalgamate various data sources such as imaging, biomechanical assessments, and patient-reported outcomes to offer personalized diagnostic and therapeutic insights. Through the utilization of 3D modeling and machine learning, the digital twin may facilitate precise visualization, prediction, and individualized treatment planning. Nevertheless, it is crucial to address the ethical and practical challenges related to data privacy and ensuring fair access. As this technology progresses, it has the potential to revolutionize gynecological and obstetric care by enhancing diagnostics, customizing treatments, and increasing patient involvement.
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Identifiers
What OpenQuestion holds
Registered trials
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.