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Georgios D. Barmparis on Muck Rack

Georgios D. Barmparis

As seen in: Nature, Frontiers, Optica
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Articles

Editorial: Machine-learning-assisted photonic design: from fundamental physics to advanced devices

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By Georgios D. Barmparis, Giorgos P. Tsironis, Demetri Psaltis
| Frontiers
Over the past few decades, machine learning (ML) has profoundly influenced a broad range of scientific and technological disciplines, enabling the exploration of increasingly complex problems through powerful data-driven methodologies. The convergence of machine learning with photonic design represents one of the most dynamic intersections between modern computational science and fundamental physics.
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Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach - Journal of Human Hypertension

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By Georgios D. Barmparis, Konstantinos Fragkiadakis, Eleni Angelaki
| Nature Verified
Abstract Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based analysis of 12-lead electrocardiograms (ECGs) can already detect arrhythmias and hypertension.
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Deep learning-assisted frequency-domain photoacoustic microscopy

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By Giannis Zacharakis, Nikolaos Kokosalis, Georgios D. Barmparis, Eirini Smaro Giosa
| Optica Verified
Abstract Frequency-domain photoacoustic microscopy (FD-PAM) constitutes a powerful cost-efficient imaging method integrating intensity-modulated laser beams for the excitation of single-frequency photoacoustic waves. Nevertheless, FD-PAM provides an extremely small signal-to-noise ratio (SNR), which can be up to two orders of magnitude lower than the conventional time-domain (TD) systems.
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