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Marcin Rojek on Muck Rack

Marcin Rojek

As seen in: Medium, Nature, MDPI, Dialnet - Universidad de La Rioja, Bitebi.com
Co-Founder @byteLAKEGlobal | Building Practical AI that solves real problems | Industrial AI, Explainable AI & AI Agents
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Articles

Detection, localization, and measurement of endotracheal tube positioning on adults’ chest X-ray: developing a prediction model

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By Jakub Kufel, Piotr Dudek, Michał Bielówka, Mikołaj Magiera, Marcin Rojek, Iga Paszkiewicz, Katarzyna Gruszczyńska, Joanna Polanska, Magdalena Stencel
| Nature Verified
Abstract Accurate placement of the endotracheal tube (ETT) is critical for ensuring optimal care for patients requiring mechanical ventilation and preventing potential complications. ETT positioning can be assessed using several methods, with chest X-ray (CXR) being the most precise. Radiologists evaluate whether the ETT requires adjustment by measuring the distance between the distal tip of the ETT and the tracheal carina.
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Plasma circulating free DNA in chronic schizophrenia: a case-control study

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By Piotr Lewandowski, Marcin Rojek, Szymon Florek, Piotr Gorczyca, Magdalena Piegza, Kamila Meca
| Nature Verified
Abstract Circulating cell-free DNA (cf-DNA) reflects ongoing cell injury and inflammation, but its role in schizophrenia remains unclear. We conducted a case-control study of 33 clinically stabilized patients with chronic schizophrenia and 30 healthy volunteers. Plasma cf-DNA was quantified by fluorometry and droplet digital PCR (ddPCR) targeting nuclear (cf-nucDNA) and mitochondrial (cf-mtDNA) genomes.
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A Machine Learning Approach to Valve Plate Failure Prediction in Piston Pumps Under Imbalanced Data Conditions: Comparison of Data Balancing Methods

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By Marcin Rojek, Marcin Blachnik
| Preprints.org
This version is not peer-reviewed. Marcin Rojek  *,Marcin Blachnik  * Marcin Rojek  *,Marcin Blachnik  * Submitted: 17 September 2025 Posted: 19 September 2025 You are already at the latest version This article focuses on the problem of building a real-world predictive maintenance system for hydraulic piston pumps. Particular attention is given to the issue of limited data availability regarding the failure state of systems with a damaged valve plate.
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