A Machine Learning Approach to Gene Expression in Hypertrophic Cardiomyopathy

These findings suggest that reduced expression of apoptotic genes may indicate a protective cellular mechanism, which could serve as a biomarker for disease progression. Further studies are needed to investigate the potential for therapeutic modulation of these pathways to improve patient outcomes.

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Publication Details

Journal
Pharmaceuticals
Published
2024-10-12
DOI
https://doi.org/10.3390/ph17101364
Citations
2
Primary Topic
Cardiomyopathy and Myosin Studies
Type
article
Field-Weighted Citation Impact
0.80
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article

A Machine Learning Approach to Gene Expression in Hypertrophic Cardiomyopathy

Nenad Filipović, Bogdan Miličević, Katarina Virijević, Jelena Košarić et al.
2 citations
Pharmaceuticals
Cardiomyopathy and Myosin Studies
0.80
article

A Machine Learning Approach to Gene Expression in Hypertrophic Cardiomyopathy

Nenad Filipović, Bogdan Miličević, Katarina Virijević, Jelena Košarić, Marko Živanović, Stefan Seman, Tamara Mladenović, Vesna Stanković, Milorad Tešić, Safi Ur Rehman Qamar, Ivana V. Novaković, Jelena Pavić, Dejana Popović, Lazar Velicki, Andrej Preveden, Irena Tanasković, Ognjen Pavić
article en
2 citations

Abstract

These findings suggest that reduced expression of apoptotic genes may indicate a protective cellular mechanism, which could serve as a biomarker for disease progression. Further studies are needed to investigate the potential for therapeutic modulation of these pathways to improve patient outcomes.

PharmaceuticalsVol. 17(10)
Mayo Clinic (US), University of Kragujevac (RS), University of Novi Sad (RS), University of Belgrade (RS), Institute for Cardiovascular Diseases of Vojvodina (RS)
Good health and well-being
Openalex Percentile: Top 23%
Cardiomyopathy and Myosin Studies
0.80
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A Machine Learning Approach to Gene Expression in Hypertrophic Cardiomyopathy — Nenad Filipović, Bogdan Miličević, et al. · Pharmaceuticals (2024) | TGRS Research Map | TGRS