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Related Concept Videos

Pneumothorax-I01:26

Pneumothorax-I

579
A pneumothorax is a condition where air builds up in the space between the lung and the chest wall, causing the lung to collapse. This condition arises when air enters the space between the parietal and visceral pleura, disrupting the negative pressure essential for lung inflation. This can lead to a partial or complete collapse of the lung.
Pneumothorax can be even further classified as spontaneous, traumatic, and tension pneumothorax.
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Pneumothorax-II01:27

Pneumothorax-II

435
Pneumothorax is a medical condition defined by the buildup of air in the pleural space between the lungs and the chest wall. This accumulation of air can lead to partial or complete lung collapse, resulting in a range of clinical manifestations. Understanding the clinical presentation and effective management strategies is crucial for healthcare professionals in providing timely and appropriate care to individuals with pneumothorax.
Clinical Manifestations:
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Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

918
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
918
Pulse rhythm01:30

Pulse rhythm

972
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
972

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A deep learning-based system capable of detecting pneumothorax via electrocardiogram.

Chiao-Chin Lee1, Chin-Sheng Lin1, Chien-Sung Tsai2

  • 1Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.

European Journal of Trauma and Emergency Surgery : Official Publication of the European Trauma Society
|February 15, 2022
PubMed
Summary

An artificial intelligence (AI) system can identify pneumothorax using electrocardiograms (ECGs) before imaging. This AI demonstrated high accuracy, potentially aiding early diagnosis in emergency settings.

Keywords:
Artificial intelligenceDeep learningECG12NetElectrocardiogramOut-of-hospitalPneumothorax

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Area of Science:

  • Medical Artificial Intelligence
  • Cardiology
  • Pulmonology

Background:

  • Pneumothorax, a condition of collapsed lung, requires timely diagnosis and intervention.
  • Current diagnostic methods for pneumothorax often involve radiological imaging, which may cause delays in critical care.
  • The potential of electrocardiograms (ECGs) in non-invasively detecting various medical conditions is increasingly recognized.

Purpose of the Study:

  • To evaluate the efficacy of an artificial intelligence (AI) system in identifying pneumothorax using ECG data.
  • To determine if AI-based ECG analysis can facilitate early pneumothorax detection prior to definitive radiological examination.

Main Methods:

  • A retrospective study utilized 107 ECGs from 98 pneumothorax patients and 132,127 control ECGs.
  • A deep learning model (DLM) was trained on 80% of the data and validated on the remaining 20%.
  • Model performance was benchmarked against three physicians in a human-machine competition.

Main Results:

  • The DLM achieved high performance with an area under the receiver operating characteristic curve (AUC) of 0.947 in the validation cohort.
  • The AI system demonstrated superior sensitivity (94.7%) and specificity (88.1%) compared to physicians.
  • Lead I ECG alone was highly effective, and incorporating patient characteristics further improved performance (AUC 0.994).

Conclusions:

  • An AI system utilizing 12-lead ECGs shows significant promise for early pneumothorax identification.
  • The AI system's performance with lead I ECG alone is comparable to using all 12 leads.
  • This AI technology could serve as a valuable tool to assist healthcare systems in the rapid detection of pneumothorax.