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The processes and benefits of sharing clinical data

Research output: Non-textual formLecture

Original languageEnglish
Media of outputOnline
Publication statusPublished - 28 Jul 2016
EventThe Data Dialogue: Time to Share: Navigating Boundaries & Benefits - Murray Edwards College, Cambridge, United Kingdom
Duration: 28 Jul 2016 → …

Bibliographical note

This presentation was given at the "Data Dialogue: Time to Share: Navigating Boundaries & Benefits" event, organised by Science and Engineering South.


King's Authors


  • The Data Dialogue

    Activity: Participating in or organising an eventParticipation in conference


  • Development of a system for automated processing of physiological monitoring data

    Impact: Health Impacts


The Respiratory Rate Estimation project aims to assess methods for automated respiratory rate (RR) monitoring of hospital patients. It consists of a series of studies of different algorithms for RR estimation from clinical data, complimented by the provision of publicly available datasets and resources.

Ethical procedures were followed to provide accountability for data collection, including obtaining approval from a Research Ethics Committee, written informed consent from each participant, and public dissemination of the protocol a priori.

Data were anonymised within the NHS to ensure confidentiality, before transfer to a university. The dataset was cleaned and formatted intuitively to allow external researchers to easily re-use it.A toolbox of algorithms was constructed to allow a systematic comparison. The dataset, toolbox, analysis code and results are publicly available. These resources facilitate transparency, reproducibility, and ongoing peer review of the research. Other publicly available datasets are now compatible with the toolbox, providing foundations for large-scale analyses across multiple datasets.

The accessibility of the dataset and resources will soon be widened by publication of an educational tutorial aimed at clinicians and data scientists, with exemplary analyses and code. Patients, students and researchers could all benefit from the sharing of this dataset.

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