Unveiling MiRNA-124 as a biomarker in hypertrophic cardiomyopathy: An innovative approach using machine learning and intelligent data analysis

Pisklova, Maria; Osmak, German

doi:10.1016/j.ijcard.2024.132220

International Journal of Cardiology

2024

DOI: 10.1016/j.ijcard.2024.132220

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Unveiling MiRNA-124 as a biomarker in hypertrophic cardiomyopathy: An innovative approach using machine learning and intelligent data analysis

Maria Pisklova,

German Osmak

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2024

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Cited by 3 publications

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miR-124-3p may exert its effects in hypertrophic cardiomyopathy by inhibiting cardiomyocyte apoptosis

Yan,

Weng,

Guo

2024

International Journal of Cardiology

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miR-124-3p may exert its effects in hypertrophic cardiomyopathy by inhibiting cardiomyocyte apoptosis

Yan,

Weng,

Guo

2024

International Journal of Cardiology

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Risk prediction modeling in the context of machine learning for injury prevention in sports

Zhang,

Zhao,

Xie

2024

Applied Mathematics and Nonlinear Sciences

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Machine learning plays an increasingly important role in the field of disease risk prediction due to its optimization advantages. This paper proposes deep confidence network optimization based on the early warning model constructed by the neural network and chooses the restricted Boltzmann machine and backpropagation algorithm as the theoretical basis of deep confidence network construction. The deep confidence network is established through the construction and stacking of RBM, and backpropagation is used to fine-tune the network parameters to generate the model. Combined with the incidence rate data of sports injuries of physical education majors and the injury classification of the deep confidence network algorithm, the test data application results verify that the algorithm has a good effect of early warning in case of sports injuries. The survey data showed that the incidence of sports injuries was 228%, and the main risk indicators causing sports injuries were not drinking alcohol (95.31%) and incorrect sports knowledge (92.09%). The model correctly predicted 94.15% (95% CI: 0.9204, 0.9608) with sensitivity and specificity: 0.954 and 0.923, respectively.

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Cardiomyopathies: The Role of Non-Coding RNAs

Carabetta,

Siracusa,

Leo

et al. 2024

ncRNA

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Cardiomyopathies are the structural and functional disorders of the myocardium. Etiopathogenesis is complex and involves an interplay of genetic, environmental, and lifestyle factors eventually leading to myocardial abnormalities. It is known that non-coding (Nc) RNAs, including micro (mi)-RNAs and long non-coding (lnc) RNAs, play a crucial role in regulating gene expression. Several studies have explored the role of miRNAs in the development of various pathologies, including heart diseases. In this review, we analyzed various patterns of ncRNAs expressed in the most common cardiomyopathies: dilated cardiomyopathy, hypertrophic cardiomyopathy and arrhythmogenic cardiomyopathy. Understanding the role of different ncRNAs implicated in cardiomyopathic processes may contribute to the identification of potential therapeutic targets and novel risk stratification models based on gene expression. The analysis of ncRNAs may also be helpful to unveil the molecular mechanisms subtended to these diseases.

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Unveiling MiRNA-124 as a biomarker in hypertrophic cardiomyopathy: An innovative approach using machine learning and intelligent data analysis

Cited by 3 publications

References 36 publications

miR-124-3p may exert its effects in hypertrophic cardiomyopathy by inhibiting cardiomyocyte apoptosis

miR-124-3p may exert its effects in hypertrophic cardiomyopathy by inhibiting cardiomyocyte apoptosis

Risk prediction modeling in the context of machine learning for injury prevention in sports

Cardiomyopathies: The Role of Non-Coding RNAs

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