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February 6, 2026European Heart Journal0 citations

Screening For Heart Failure Using Pulse Oximetry And Machine Learning

Screening for heart failure using simple pulse oximetry in outpatient care

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Authors

ABA BohmJJJana JankovaJLJ Lucka

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Overview

Develops a novel screening method for heart failure using pulse oximetry, indicating significant potential for outpatient care.

Key Points

  • The aim is to establish an accessible and effective screening method for heart failure using pulse oximetry.
  • Included patients attending routine ambulatory check-ups.
  • Recorded photoplethysmographic signals with a finger pulse oximeter.
  • Performed signal quality evaluation including noise removal and artifact detection.
  • Extracted 57 features from the PPG signals for machine learning classification.
  • Involved 386 patients, with 243 diagnosed with heart failure.
  • The Random Forest Classifier achieved an average c-statistics of 0.89 for HF detection.
  • Observed sensitivities and specificities at 0.86 and 0.76 respectively.

Cite This Study

Bohm et al. (2025) studied this question.

synapsesocial.com/papers/698585aa8f7c464f230093dehttps://doi.org/10.1093/eurheartj/ehaf784.1407
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A photoplethysmography-based algorithm for early atrial fibrillation detection in heart failure telemonitoring2026
  2. 2Machine learning-based screening of heart failure using the integrated features of electrocardiogram and phonocardiogram: a multicenter study in China2025
  3. 3Machine learning-based screening of heart failure using the integrated features of electrocardiogram and phonocardiogram: a multicenter study in China2025
  4. 4Detecting heart failure using wearables: a pilot study2020 · 26 citations
  5. 5Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms2024 · 24 citations