Use of genetic programming to diagnose venous thromboembolism in the emergency department

Milo Engoren, Jeffrey Kline

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Pulmonary thromboembolism as a cause of respiratory complaints is frequently undiagnosed and requires expensive imaging modalities to diagnose. The objective of this study was to determine if genetic programming could be used to classify patients as having or not having pulmonary thromboembolism using exhaled ventilatory and gas indices as genetic material. Using a custom-built exhaled oxygen and carbon dioxide analyzer; exhaled flows, volumes, and gas partial pressures were recorded from patients for a series of deep exhalation and 30 s tidal volume breathing. A diagnosis of pulmonary embolism was made by contrast-enhanced computerized tomography angiography of the chest and indirect venography supplemented by 90-day follow-up. Genetic programming developed a series of genomes comprising genes of exhaled CO 2, O 2, flow, volume, vital signs, and patient demographics from these data and their predictions were compared to the radiological results. We found that 24 of 178 patients had pulmonary embolism. The best genome consisted of four genes: the minimum flow rate during the third 30 s period of tidal breathing, the average peak exhaled CO 2 during the first 30 s period of tidal breathing, the average peak of the exhaled O 2 during the first 30 s period of tidal breathing, and the average peak exhaled CO 2 during the fourth period of tidal breathing, which immediately followed a deep exhalation. This had 100% sensitivity and 91% specificity on the construction population and 100% and 82%, respectively when tested on the separate validation population. Genetic programming using only data obtained from exhaled breaths was very accurate in classifying patients with suspected pulmonary thromboembolism.

Original languageEnglish (US)
Pages (from-to)39-51
Number of pages13
JournalGenetic Programming and Evolvable Machines
Volume9
Issue number1
DOIs
StatePublished - Mar 2008
Externally publishedYes

Fingerprint

Genetic programming
Genetic Programming
Emergency
Genes
Genome
Computerized Tomography
Gene
Angiography
Computerized tomography
Series
Carbon Dioxide
Gases
Partial pressure
Flow Rate
Modality
Specificity
Immediately
Oxygen
Carbon dioxide
Classify

Keywords

  • Capnometry
  • Genetic programming
  • Oximetry
  • Pulmonary embolism
  • Venous thromboembolic disease

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Use of genetic programming to diagnose venous thromboembolism in the emergency department. / Engoren, Milo; Kline, Jeffrey.

In: Genetic Programming and Evolvable Machines, Vol. 9, No. 1, 03.2008, p. 39-51.

Research output: Contribution to journalArticle

@article{aa5dc4ddf3cd46c99a8f2420c226dc6d,
title = "Use of genetic programming to diagnose venous thromboembolism in the emergency department",
abstract = "Pulmonary thromboembolism as a cause of respiratory complaints is frequently undiagnosed and requires expensive imaging modalities to diagnose. The objective of this study was to determine if genetic programming could be used to classify patients as having or not having pulmonary thromboembolism using exhaled ventilatory and gas indices as genetic material. Using a custom-built exhaled oxygen and carbon dioxide analyzer; exhaled flows, volumes, and gas partial pressures were recorded from patients for a series of deep exhalation and 30 s tidal volume breathing. A diagnosis of pulmonary embolism was made by contrast-enhanced computerized tomography angiography of the chest and indirect venography supplemented by 90-day follow-up. Genetic programming developed a series of genomes comprising genes of exhaled CO 2, O 2, flow, volume, vital signs, and patient demographics from these data and their predictions were compared to the radiological results. We found that 24 of 178 patients had pulmonary embolism. The best genome consisted of four genes: the minimum flow rate during the third 30 s period of tidal breathing, the average peak exhaled CO 2 during the first 30 s period of tidal breathing, the average peak of the exhaled O 2 during the first 30 s period of tidal breathing, and the average peak exhaled CO 2 during the fourth period of tidal breathing, which immediately followed a deep exhalation. This had 100{\%} sensitivity and 91{\%} specificity on the construction population and 100{\%} and 82{\%}, respectively when tested on the separate validation population. Genetic programming using only data obtained from exhaled breaths was very accurate in classifying patients with suspected pulmonary thromboembolism.",
keywords = "Capnometry, Genetic programming, Oximetry, Pulmonary embolism, Venous thromboembolic disease",
author = "Milo Engoren and Jeffrey Kline",
year = "2008",
month = "3",
doi = "10.1007/s10710-007-9050-x",
language = "English (US)",
volume = "9",
pages = "39--51",
journal = "Genetic Programming and Evolvable Machines",
issn = "1389-2576",
publisher = "Springer New York",
number = "1",

}

TY - JOUR

T1 - Use of genetic programming to diagnose venous thromboembolism in the emergency department

AU - Engoren, Milo

AU - Kline, Jeffrey

PY - 2008/3

Y1 - 2008/3

N2 - Pulmonary thromboembolism as a cause of respiratory complaints is frequently undiagnosed and requires expensive imaging modalities to diagnose. The objective of this study was to determine if genetic programming could be used to classify patients as having or not having pulmonary thromboembolism using exhaled ventilatory and gas indices as genetic material. Using a custom-built exhaled oxygen and carbon dioxide analyzer; exhaled flows, volumes, and gas partial pressures were recorded from patients for a series of deep exhalation and 30 s tidal volume breathing. A diagnosis of pulmonary embolism was made by contrast-enhanced computerized tomography angiography of the chest and indirect venography supplemented by 90-day follow-up. Genetic programming developed a series of genomes comprising genes of exhaled CO 2, O 2, flow, volume, vital signs, and patient demographics from these data and their predictions were compared to the radiological results. We found that 24 of 178 patients had pulmonary embolism. The best genome consisted of four genes: the minimum flow rate during the third 30 s period of tidal breathing, the average peak exhaled CO 2 during the first 30 s period of tidal breathing, the average peak of the exhaled O 2 during the first 30 s period of tidal breathing, and the average peak exhaled CO 2 during the fourth period of tidal breathing, which immediately followed a deep exhalation. This had 100% sensitivity and 91% specificity on the construction population and 100% and 82%, respectively when tested on the separate validation population. Genetic programming using only data obtained from exhaled breaths was very accurate in classifying patients with suspected pulmonary thromboembolism.

AB - Pulmonary thromboembolism as a cause of respiratory complaints is frequently undiagnosed and requires expensive imaging modalities to diagnose. The objective of this study was to determine if genetic programming could be used to classify patients as having or not having pulmonary thromboembolism using exhaled ventilatory and gas indices as genetic material. Using a custom-built exhaled oxygen and carbon dioxide analyzer; exhaled flows, volumes, and gas partial pressures were recorded from patients for a series of deep exhalation and 30 s tidal volume breathing. A diagnosis of pulmonary embolism was made by contrast-enhanced computerized tomography angiography of the chest and indirect venography supplemented by 90-day follow-up. Genetic programming developed a series of genomes comprising genes of exhaled CO 2, O 2, flow, volume, vital signs, and patient demographics from these data and their predictions were compared to the radiological results. We found that 24 of 178 patients had pulmonary embolism. The best genome consisted of four genes: the minimum flow rate during the third 30 s period of tidal breathing, the average peak exhaled CO 2 during the first 30 s period of tidal breathing, the average peak of the exhaled O 2 during the first 30 s period of tidal breathing, and the average peak exhaled CO 2 during the fourth period of tidal breathing, which immediately followed a deep exhalation. This had 100% sensitivity and 91% specificity on the construction population and 100% and 82%, respectively when tested on the separate validation population. Genetic programming using only data obtained from exhaled breaths was very accurate in classifying patients with suspected pulmonary thromboembolism.

KW - Capnometry

KW - Genetic programming

KW - Oximetry

KW - Pulmonary embolism

KW - Venous thromboembolic disease

UR - http://www.scopus.com/inward/record.url?scp=39849100312&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=39849100312&partnerID=8YFLogxK

U2 - 10.1007/s10710-007-9050-x

DO - 10.1007/s10710-007-9050-x

M3 - Article

VL - 9

SP - 39

EP - 51

JO - Genetic Programming and Evolvable Machines

JF - Genetic Programming and Evolvable Machines

SN - 1389-2576

IS - 1

ER -