ArticleScientific data2022
VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
89 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Wearable Blood Pressure Monitoring Devices: Understanding Heterogeneity in Design and Evaluation.IEEE transactions on bio-medical engineering · 2024Pooled it
- Non-invasive continuous versus intermittent oscillometric arterial pressure monitoring and maternal hypotension during cesarean delivery: a randomized controlled trial.Scientific reports · 2026Trial
- Comparison between upper body and full underbody forced-air warming blanket in pediatric patients undergoing cardiovascular interventions under general anesthesia: a randomized controlled trial.BMC anesthesiology · 2025Trial
- Prolonged Length of Stay After Lung Resection: A Prediction Model That Loses Accuracy Across Hospitals, with No Added Benefit from Blood Pressure Data.Journal of clinical medicine · 2026Article
- Intraoperative Arterial Waveform Morphology Trajectories and Prediction of Postoperative Acute Kidney Injury: A Latent-Class Analysis of the VitalDB Registry.Journal of clinical medicine · 2026Article
- Healthcare-Based Multimodal Recovery Prediction for the Warfighter: A Retrospective Study.Military medicine · 2026Article
- Arterial blood pressure waveform reconstruction estimation from PPG using TCN-BiLSTM.American heart journal plus : cardiology research and practice · 2026Article
- Systemic fragility in European total intravenous anesthesia delivery and opportunities for resilient real-time decision support.Communications medicine · 2026Review
- Causal Effect and Personalization of Intraoperative Hypotension Burden on Postoperative Acute Kidney Injury: A Doubly Robust Analysis of the VitalDB Cohort.Journal of personalized medicine · 2026Article
- A Novel Method for Cardiac Output and Vascular Parameters Estimation Using Peripheral Arterial Waveforms: Integrating Windkessel Model viaAnnals of biomedical engineering · 2026Article
- A systematic evaluation of uncertainty quantification techniques in deep learning: a case study in photoplethysmography signal analysis.Machine learning. Health · 2026Article
- A Multitask Time-Frequency Deep Learning Approach for Anesthesia Depth Monitoring and Transition Prediction.Diagnostics (Basel, Switzerland) · 2026Article
- Integration of intraoperative data in interpretable machine learning models to predict postoperative AKI in noncardiac surgery patients.JAMIA open · 2026Article
- Cohort profile: PeRiOperative sTress risk assEssment and Clinical decision cohorT (PROTECT), a multi-center observational study based on real-world data.BMC geriatrics · 2026Observational
- Early prediction of intraoperative hypotension: development and validation of the HypoBridCast hybrid deep learning model.BMC anesthesiology · 2026Article
- Induction-Phase Peripheral Perfusion Dynamics and Rocuronium Neuromuscular Blockade Onset: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- End-of-surgery prediction of postoperative infectious complications from intraoperative vital-sign dynamics.NPJ digital medicine · 2026Article
- Shape and amplitude decoupling in pulsatile physiological signal synthesis and its evaluation.Nature communications · 2026Article
- Multimodal PPG-Based Arrhythmia Detection Using a CLIP-Initialized Multi-Task U-Net and LLM-Assisted Reporting.Sensors (Basel, Switzerland) · 2026Article
- Evaluating cross-dataset transfer learning for photoplethysmography-based blood pressure estimation.Scientific reports · 2026Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for experienced anesthesiologists. Recent advanced machine learning technologies have shown promising results in biosignal analysis, however, research and development in this area is relatively slow due to the lack of biosignal datasets for machine learning. The VitalDB (Vital Signs DataBase) is an open dataset created specifically to facilitate machine learning studies related to monitoring vital signs in surgical patients. This dataset contains high-resolution multi-parameter data from 6,388 cases, including 486,451 waveform and numeric data tracks of 196 intraoperative monitoring parameters, 73 perioperative clinical parameters, and 34 time-series laboratory result parameters. All data is stored in the public cloud after anonymization. The dataset can be freely accessed and analysed using application programming interfaces and Python library. The VitalDB public dataset is expected to be a valuable resource for biosignal research and development.
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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.