AIMC Topic: Oxygen Consumption

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Optimizing intervertebral disc cell metabolic phenotyping with machine learning and artificial neural networks.

Scientific reports
Biological phenotyping of cellular metabolism is essential for deciphering health and disease states. The Seahorse XF analyzer enables direct measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), providing insight ...

Interpretable deep learning for personalized energy expenditure prediction using ECG and acceleration signals in incremental exercise.

Scientific reports
Energy expenditure (EE) assessment is crucial in both sports science and health management. However, current EE prediction models often overlook individual differences and lack dynamic correlation analysis between multi-modal data and EE. Building up...

Deep learning prediction of peak oxygen uptake in patients with coronary heart disease: a retrospective study.

BMJ open
OBJECTIVE: To develop and validate prediction models for peak oxygen uptake (VO₂peak) in patients with coronary heart disease (CHD) using submaximal cardiopulmonary exercise testing (CPET) indicators and deep learning methods.

VO Max in Clinical Cardiology: Clinical Applications, Evidence Gaps, and Future Directions.

Current cardiology reports
PURPOSE OF REVIEW: VO₂ max is a fundamental marker of cardiorespiratory fitness with substantial prognostic and diagnostic value within the field of cardiology. This review analyzes current and emerging evidence regarding its clinical uses, highlight...

Association between the COVID-19 pandemic and cardiopulmonary function in acute coronary syndrome patients without SARS-CoV-2 infection.

Scientific reports
The COVID-19 pandemic disrupted cardiovascular disease management. This single-center cross-sectional cohort study evaluated cardiopulmonary function changes in acute coronary syndrome (ACS) patients post-percutaneous coronary intervention (PCI) with...

Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.

Sensors (Basel, Switzerland)
The physical workload evaluation of construction activities will help to prevent excess physical fatigue or overexertion. The workload determination involves measuring physiological responses such as oxygen uptake (VO) while performing the work. The ...

Estimating oxygen uptake in simulated team sports using machine learning models and wearable sensor data: A pilot study.

PloS one
Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable se...

Automated mitochondrial oxygen consumption (mitoVO) analysis via a bi-directional long short-term memory neural network.

Journal of clinical monitoring and computing
Monitoring in vivo mitochondrial oxygen tension (mitoPO) enables the measurement of mitochondrial oxygen consumption (mitoVO), providing deeper insights into the skin's mitochondrial environment. However, current mitoVO analysis often relies on manua...

Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

Biosensors
The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minute (VO) mL/kg/min, is a critical metric for evaluating cardiovascular health, metabolic status, and respiratory function. Specifically, VO is a powerf...

Interpretation of cardiopulmonary exercise test by GPT - promising tool as a first step to identify normal results.

Expert review of respiratory medicine
BACKGROUND: Cardiopulmonary exercise testing (CPET) is used in the evaluation of unexplained dyspnea. However, its interpretation requires expertise that is often not available. We aim to evaluate the utility of ChatGPT (GPT) in interpreting CPET res...