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Related Concept Videos

Lung Capacity01:47

Lung Capacity

51.5K
The air in the lungs is measured in volumes and capacities. Lung volume measures reflect the amount of air taken in, released, or left over after a lung function, like a single inhalation. Lung capacity measures are sums of two or more lung volume measures.
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Respiratory Volumes01:15

Respiratory Volumes

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Respiratory volumes are crucial metrics, meticulously measured to quantify the air exchanged in and out of the lungs during various phases of the breathing cycle. These precise measurements are vital for assessing lung function, diagnosing respiratory conditions, and monitoring overall respiratory health. Each parameter provides specific insights into the mechanics of breathing and the functional capacity of the lungs.
Tidal Volume (TV) Tidal volume (TV) is the air inhaled or exhaled in a...
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Respiratory Volumes and Capacities01:22

Respiratory Volumes and Capacities

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The respiratory system is responsible for the intake of oxygen and the expulsion of carbon dioxide from the body. Respiratory volumes describe the volume of air in the lungs at different phases of the respiratory cycle. Tidal volume is the air breathed in and out during normal, quiet breathing. Inspiratory reserve volume is the air that can be forcefully inspired beyond the tidal volume. In contrast, expiratory reserve volume refers to the air that can be expelled from the lungs after a normal...
2.8K
Respiratory Volumes and Capacities I01:26

Respiratory Volumes and Capacities I

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Assessing the respiratory rate and rhythm for a complete minute is crucial for evaluating the breathing pattern. Even a minor increase in the patient's average respiratory rate, by as little as three to five breaths per minute, is an early and vital indicator of respiratory distress. Patients with a respiratory rate exceeding twenty-four breaths per minute require close monitoring to determine the physiological alterations. This careful observation is essential for prompt recognition and...
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Pulmonary Function Tests01:25

Pulmonary Function Tests

437
Pulmonary Function Tests (PFTs)
Pulmonary Function Tests are crucial diagnostic tools for assessing respiratory function, particularly in patients with chronic respiratory disorders. They comprehensively evaluate lung volumes, ventilatory function, breathing mechanics, diffusion, and gas exchange. These tests help diagnose pulmonary diseases and play a significant role in monitoring disease progression, evaluating disability, and assessing response to therapy.
PFTs involve using a spirometer, a...
437
Respiratory Capacities01:24

Respiratory Capacities

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Respiratory capacities are crucial indicators of lung function, representing the maximum amount of air an individual's respiratory system can handle during various breathing phases.
One key metric is the Inspiratory Capacity (IC), which represents the maximum amount of air that can be inhaled with full effort. IC is calculated by summing the tidal volume and inspiratory reserve volume, typically ranging from 2.4 to 3.6 liters.
The Functional Residual Capacity (FRC) represents the air in the...
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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and

Scott A Helgeson1, Zachary S Quicksall2, Patrick W Johnson2

  • 1Division of Pulmonary and Critical Care Medicine, Mayo Clinic, 4500 San Pablo Road S, Jacksonville, FL, 32224, United States, 1 9049532000.

JMIR AI
|July 3, 2025
PubMed
Summary
This summary is machine-generated.

Machine learning models can estimate static lung volumes using spirometry data, improving respiratory diagnosis where advanced testing is unavailable. This AI approach enhances pulmonary function assessment.

Keywords:
AIMLartificial intelligencedatabaselunglung capacitylung diseaselung volumemachine learningpulmonarypulmonary function testrespiratoryspirometerspirometrytotal lung capacity

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Area of Science:

  • Pulmonary Medicine
  • Artificial Intelligence
  • Data Science

Background:

  • Spirometry is a common tool for diagnosing obstructive lung disease.
  • Advanced lung function testing like body plethysmography is needed for detailed assessments but is not widely available.
  • There is a need for methods to estimate static lung volumes using readily available spirometry data.

Purpose of the Study:

  • To develop artificial intelligence (AI) algorithms for estimating lung volumes and capacities from spirometry measurements.
  • To leverage machine learning techniques to extract clinically relevant information from spirometry data.

Main Methods:

  • Utilized a large dataset of spirometry and lung volume measurements from the Mayo Clinic pulmonary function test database (2001-2022).
  • Applied various machine learning algorithms, including generalized linear models, random forests, extremely randomized trees, gradient-boosted trees, and XGBoost.
  • Trained and evaluated models on a substantial cohort of 121,498 pulmonary function tests.

Main Results:

  • Machine learning models demonstrated robust performance in estimating lung volumes and capacities.
  • Low root mean square error and mean absolute error were observed across predicted lung volumes.
  • High area under the receiver operating characteristic curve values (0.81-0.99) indicated strong discriminatory capacity.

Conclusions:

  • AI-based spirometry analysis shows significant potential for clinical application.
  • These models can aid in the accurate diagnosis and prognosis of respiratory conditions.
  • The approach is particularly valuable in settings with limited access to advanced lung volume measurement tools like body plethysmography.