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Computational Framework to Interpret Chest X-rays and Diagnose Pneumonia

Population Size

Not reported
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Years

2018 - 2020

Years statistic card

Associated BioSamples

None/not available

Associated BioSamples statistic card

Geographic coverage

United Kingdom

Geographic coverage statistic card

Lead time

Variable

Lead time statistic card

Summary

The aim of the project is to construct a computational framework to automatically and systematically interpret paediatric chest X-rays to diagnose pneumonia.

Documentation

It is estimated that 95% of the two million deaths due to pneumonia occur in developing countries. In Bangladesh alone, six million cases of pneumonia are diagnosed every year. Unfortunately, diagnostic methods to date lack sensitivity or are difficult to fully standardized. The lack of a reliable diagnostic hampers the execution of evidence based interventions, impacting the monitoring of interventions, like vaccines.

The “gold standard” for defining pneumonia are chest X-rays. However, the interpretations are subjective, sometimes requiring multiple radiologists/clinicians to reach a conclusive diagnosis. As there are few well-trained radiologists/clinicians in resource-poor settings, having a tool to aid in the diagnosis of pneumonia would be invaluable in the impact monitoring of interventions.

The aim of the project is to construct a computational framework to automatically and systematically interpret paediatric chest X-rays to diagnose pneumonia.

For further information, see: https://www.ed.ac.uk/usher/respire/acute-respiratory-disorders/interpret-chest-x-rays

Dataset type

Health and disease

Dataset sub-type

Not applicable

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Findings

1

Count

31 Dec 2020

Provenance

Purpose of dataset collection

Study

Collection source setting

Community

Image contrast

Not stated

Biological sample availability

None/not available

Details

Publishing frequency

Static

Version

2.0.0

Modified

08/10/2024

Distribution release date

31/12/2020

Citation Requirements

RESPIRE

Coverage

Start date

01/07/2018

End date

31/12/2020

Time lag

Not applicable

Geographic coverage

United Kingdom

Maximum age range

5

Accessibility

Language

en

Controlled vocabulary

LOCAL

Format

text

Data Access Request

Dataset pipeline status

Not available

Time to dataset access

Variable

Access method category

Varies based on project

Access service description

Access service varies on a project-by-project basis. Contact the RESPIRE team for further in formation

Jurisdiction

GB-ENG, GB-SCT, GB-WLS

Data use limitation

General research use

Data Controller

BREATHE

Dataset Types: Health and disease


Collection Sources: Community

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