Dmitry V. Dylov

ComputAgeBench benchmarks epigenetic aging clocks by comparing 13 models on 66 harmonized blood DNA methylation datasets to evaluate their ability to distinguish healthy individuals from those with aging-accelerating conditions.

The paper analyzes how epistemic uncertainty affects the reliability of aging clocks in predicting rejuvenation effects during cellular reprogramming.

This paper introduces deep learning methods to improve EEG spatial resolution by translating scalp potentials to cortical sources using CNN-based solvers trained on synthetic data.

This paper uses optical spectroscopy and machine learning to rapidly identify malignant tissue in cancer biopsies, achieving high sensitivity and specificity.