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Zholdas Buribayev

As seen in: ScienceDaily, MDPI
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Articles

Phase-specific kidney graft failure prediction with machine learning model

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By Amankeldi Salybekov, Markus Wolfien, Ainur Yerkos, Zholdas Buribayev
| tu-dresden.de
BACKGROUND: Accurate prediction of kidney graft failure at different phases post-transplantation is critical for timely intervention and long-term allograft preservation. Traditional survival models offer limited capacity for dynamic, time-specific risk estimation. Machine learning (ML) approaches, with their ability to model complex patterns, present a promising alternative.
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Epigenomic Echoes-Decoding Genomic and Epigenetic Instability to Distinguish Lung Cancer Types and Predict Relapse

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By Alexandra Baumann, Zholdas Buribayev, Olaf Wolkenhauer, Amankeldi Salybekov
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Epigenomic Echoes-Decoding Genomic and Epigenetic Instability to Distinguish Lung Cancer Types and Predict Relapse

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By Alexandra Baumann, Zholdas Buribayev, Olaf Wolkenhauer, Amankeldi Salybekov
| tu-dresden.de
Abstract External IDs PubMedCentral PMC11843950
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