Publications by authors named "J A Kanters"
Background: Machine learning-based analysis can accurately detect atrial fibrillation (AF) from photoplethysmograms (PPGs), however the computational requirements for analyzing raw PPG waveforms can be significant. The analysis of PPG-derived peak-to-peak intervals may offer a more feasible solution for smartphone deployment, provided the diagnostic utility is comparable.
Aims: To compare raw PPG waveforms and PPG-derived peak-to-peak intervals as input signals for machine learning detection of AF.
Objective: Evaluate popular explanation methods using heatmap visualizations to explain the predictions of deep neural networks for electrocardiogram (ECG) analysis and provide recommendations for selection of explanations methods.
Materials And Methods: A residual deep neural network was trained on ECGs to predict intervals and amplitudes. Nine commonly used explanation methods (Saliency, Deconvolution, Guided backpropagation, Gradient SHAP, SmoothGrad, Input × gradient, DeepLIFT, Integrated gradients, GradCAM) were qualitatively evaluated by medical experts and objectively evaluated using a perturbation-based method.
Article Synopsis
- The study investigates the relationship between serum calcium levels and ventricular repolarization time, specifically the QT and JT intervals, which are important for heart health.
- Researchers conducted large-scale genome-wide analyses to explore potential interactions between calcium levels and genetic variants associated with QT and JT intervals, using over 122,000 participants.
- The results showed limited evidence for the hypothesized calcium interaction effects, suggesting that other factors, such as rare genetic variations or environmental influences, likely play a larger role in the unexplained heritability of QT and JT intervals.
Purpose: The association between thyroid dysfunction and exudative age-related macular degeneration (AMD) is unknown.
Methods: In this Danish longitudinal nationwide registry-based cohort study we included all Danish residents aged 50-100 between 2008 and 2018. Using the Danish national registries, we studied the association between thyroid dysfunction and exudative AMD.
Background: The association between type 2 diabetes and electrocardiographic (ECG) markers are incompletely explored and the dependence on diabetes duration is largely unknown. We aimed to investigate the electrocardiographic (ECG) changes associated with type 2 diabetes over time.
Methods: In this cross-sectional study, we matched people with type 2 diabetes 1:1 on sex, age, and body mass index with people without diabetes from the general population.