Hemopneumothorax detection through the process of artificial evolution - a feasibility study

Adir Sommer; Noy Mark; Gavriel D. Kohlberg; Rafi Gerasi; Linn Wagnert Avraham; Ruth Fan-Marko; Arik Eisenkraft; Dean Nachman

doi:10.1186/s40779-021-00319-2

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Hemopneumothorax detection through the process of artificial evolution - a feasibility study

RESEARCH | Updated：2023-02-28

- Hemopneumothorax detection through the process of artificial evolution - a feasibility study
- Military Medical Research Vol. 9, Issue 1, Pages: 12-20(2022)
- Affiliations：
  
  1.The Medical Corps, Israel Defense Forces (IDF), Tel Hashomer, 5262000 Ramat Gan, Israel
  2.Department of Otolaryngology - Head and Neck Surgery, University of Washington, Seattle, WA 98195, USA
  3.The Institute for Research in Military Medicine, the Faculty of Medicine, the Hebrew University of Jerusalem and the IDF Medical Corps, 9112102 Jerusalem, Israel
  4.The Hebrew University School of Medicine, 9112102 Jerusalem, Israel
  5.Department of Medicine, Hadassah Medical Center, 9112102 Jerusalem, Israel
- Author bio：
  
  * adirsommer@gmail.com
- Funds：
- DOI：10.1186/s40779-021-00319-2
  CLC：
- Published：2022-02
- Accepted：
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Sommer et al.: Hemopneumothorax detection through the process of artificial evolution - a feasibility study. Mil Med Res, 2021, 8: 27.
DOI：

Sommer et al.: Hemopneumothorax detection through the process of artificial evolution - a feasibility study. Mil Med Res, 2021, 8: 27. DOI： 10.1186/s40779-021-00319-2.

摘要

Abstract

Background:

Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techniques are not fully applicable in field conditions and on the battlefield

where situational and environmental factors may impair clinical capabilities. We aimed to assemble a device able to sample

analyze

and classify the unique acoustic signatures of pneumothorax and hemothorax.

Methods:

Acoustic data was obtained with simultaneous use of two sensitive digital stethoscopes from the chest wall of an

ex-vivo

porcine model. Twelve second samples of acoustic data were obtained from the in-house assembled digital stethoscope system during mechanical ventilation. The thoracic cavity was injected with increasing volumes of 200

400

600

800

and 1000 ml of air or saline to simulate pneumothorax and hemothorax

respectively. The data was analyzed using a multi-objective genetic algorithm that was used to develop an optimal mathematical detector through the process of artificial evolution

a cutting-edge approach in the artificial intelligence discipline.

Results:

The in-house assembled dual digital stethoscope system and developed genetic algorithm achieved an accuracy

sensitivity and specificity ranging from 64% to 100%

63% to 100%

and 63% to 100%

respectively

in classifying acoustic signal as associated with pneumothorax or hemothorax at fluid injection levels of 400 ml or more

and regardless of background noise.

Conclusions:

We present a novel

objective device for rapid diagnosis of potentially lethal thoracic injuries. With further optimization

such a device could provide real-time detection and monitoring of pneumothorax and hemothorax in battlefield conditions.

关键词

Keywords

references

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