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Related Concept Videos

Cardiac Output II: Effect of Stroke Volume on Cardiac Output01:22

Cardiac Output II: Effect of Stroke Volume on Cardiac Output

Cardiac output (CO), the amount of blood the heart pumps per minute, is a parameter in cardiovascular physiology determined by stroke volume and heart rate. Stroke volume, the amount of blood pushed from one of the ventricles per heartbeat, is influenced by preload, afterload, and contractility.
Preload
Preload refers to the initial elongation of the cardiac myocytes before contraction and is related to the volume of blood filling the heart at the end of diastole, or end-diastolic volume. The...
Regulation of Stroke Volume01:27

Regulation of Stroke Volume

The regulation of stroke volume, which is the amount of blood the heart pumps out during each heartbeat, is critical for maintaining a healthy circulatory system. Stroke volume is influenced by three main factors: preload, contractility, and afterload.
Preload refers to the degree of stretch on the heart before it contracts. It's analogous to the stretching of a rubber band; the more it's stretched, the more forcefully it snaps back. This concept is encapsulated in the Frank-Starling law of the...
Cardiac Output and Stroke Volume01:11

Cardiac Output and Stroke Volume

Cardiac output (CO) is an integral aspect of human physiology, reflecting the heart's efficiency and responsiveness to the body's needs. It represents the volume of blood that the left or right ventricle ejects into the aorta or pulmonary trunk each minute. The CO is calculated by multiplying the heart rate (HR)—the number of heartbeats per minute—by the stroke volume (SV)—the amount of blood pumped out with each heartbeat.
In an average resting adult male, the typical cardiac output averages...

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Related Experiment Videos

Evaluating and Mitigating Carbon Dioxide Equivalent Emissions in Stroke Management: A Modeling Study.

Alireza Vafaei Sadr1, Seyyed Sina Hejazian2, Ajith Vemuri2

  • 1Department of Public Health Sciences, College of Medicine Pennsylvania State University Hershey PA USA.

Journal of the American Heart Association
|July 3, 2026
PubMed
Summary

Artificial intelligence (AI) in stroke imaging has a significant carbon footprint, varying by AI model and energy source. Shifting computation to cleaner energy grids can cut emissions by over 50%.

Keywords:
artificial intelligencecarbon footprintdiagnostic imagingstrokesustainability

Related Experiment Videos

Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Environmental Science

Background:

  • Artificial intelligence (AI) offers potential improvements in stroke imaging workflows.
  • The environmental impact, specifically the carbon footprint of AI in healthcare, is not well understood.
  • Estimating CO2 equivalent (CO2eq) emissions from AI in US stroke management is crucial for evaluating mitigation strategies.

Purpose of the Study:

  • To quantify the carbon dioxide equivalent (CO2eq) emissions associated with AI use in US stroke imaging.
  • To evaluate the effectiveness of carbon-aware mitigation strategies for AI in stroke care.

Main Methods:

  • Utilized TriNetX neuroimaging data and Global Burden of Disease stroke estimates (2018-2019).
  • Modeled two AI scenarios: Minimal AI (2D classification and segmentation models) and Ideal AI (multiple 2D/3D models).
  • Calculated CO2eq emissions using state-level grid carbon intensity data.

Main Results:

  • Ideal AI generated 16,375 metric tons CO2eq/year; Minimal AI generated 7,693 metric tons CO2eq/year.
  • Computed tomography angiography and MRI were the primary contributors to emissions.
  • Relocating processing to cleaner energy states reduced Ideal AI emissions by 54.75%.

Conclusions:

  • AI-assisted stroke imaging possesses a quantifiable carbon footprint influenced by AI model complexity, imaging modality, and energy grid carbon intensity.
  • Carbon-aware computation routing presents a viable immediate strategy to reduce environmental impact while enabling continued clinical AI adoption.