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| Hlavní autoři: | , , , , , , , , , , , , , , , |
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| Médium: | Recurso digital |
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Zenodo
2026
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| Témata: | |
| On-line přístup: | https://doi.org/10.5281/zenodo.20055581 |
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- <p>This restricted dataset supports the study “Artificial Intelligence-Based Uroflowmetry Device: Prospective Clinical and Experimental Validation”. The record contains two analysis datasets used to reproduce the main statistical results of the study: (1) a de-identified participant-level clinical validation dataset and (2) a run-level peristaltic-pump bench validation dataset.</p> <p>The clinical dataset contains de-identified measurements from 50 male participants with lower urinary tract symptoms who completed same-day standard gravity-based uroflowmetry device (SG-UFD) and artificial intelligence-based uroflowmetry device (AI-UFD) assessments. The dataset includes SG-UFD, AI-UFD, OnePlus, and Redmi measurements for key uroflowmetry parameters, including Qmax, Qave, voided volume, flow time, void time, and time to maximum flow, together with derived variables used for agreement, diagnostic-accuracy, and sensitivity analyses. Direct identifiers, raw patient videos, exact clinical encounter dates, and variables that could reasonably enable participant re-identification are not included.</p> <p>The peristaltic-pump bench dataset contains run-level measurements from 60 bench experiments across five target flow levels and four waveform families. The dataset includes physical-truth measurements and corresponding AI-UFD, OnePlus, and Redmi outputs for Qmax and voided volume, supporting the bench agreement and condition-specific accuracy analyses.</p> <p>These datasets are provided for research transparency, reproducibility assessment, and qualified methodological research. Because the clinical dataset derives from human participant data and because the AI-UFD platform is undergoing clinical-trial and institutional intellectual-property procedures, all files in this record are provided under restricted access.</p> <p><strong>Access request conditions:</strong></p> <p>Access to the files is restricted. Requests will be considered from qualified researchers for non-commercial research, methodological validation, and reproducibility assessment. Requests must include the requester’s full name, institutional affiliation, institutional email address, research purpose, planned analyses, and confirmation that the data will not be used for participant re-identification, commercial product development, redistribution, or attempts to reconstruct proprietary AI-UFD software or model components.</p> <p>Access may be granted at the discretion of the corresponding authors and is subject to institutional approval, applicable ethical and data-governance requirements, confidentiality obligations, and completion of a data-use agreement where required. The files may not be redistributed to third parties without written permission from the corresponding authors.</p>