Order of importance of anatomical risk factors in Kienböck’s disease: An artificial neural network study

Asfuroğlu, Zeynel Mert; Güvenç, K.; Gümüşoğlu, E.; Ten, Barış; Eskandari, Metin Manouchehr

doi:10.1016/j.hansur.2022.02.003

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Cited by 4 publications

References 22 publications

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A decreasing failure rate model with a novel approach to enhance the artificial neural network's structure for engineering and disease data analysis

Sindhu,

Çolak,

Lone

et al. 2024

Tribology International

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A decreasing failure rate model with a novel approach to enhance the artificial neural network's structure for engineering and disease data analysis

Sindhu,

Çolak,

Lone

et al. 2024

Tribology International

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Aseptische Lunatumnekrose: Welche sind die wichtigsten anatomischen Risikofaktoren?

2022

Handchirurgie Scan

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A neural network model to screen feature genes for pancreatic cancer

Huang,

Zhou,

Zhang

et al. 2023

BMC Bioinformatics

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All the time, pancreatic cancer is a problem worldwide because of its high degree of malignancy and increased mortality. Neural network model analysis is an efficient and accurate machine learning method that can quickly and accurately predict disease feature genes. The aim of our research was to build a neural network model that would help screen out feature genes for pancreatic cancer diagnosis and prediction of prognosis. Our study confirmed that the neural network model is a reliable way to predict feature genes of pancreatic cancer, and immune cells infiltrating play an essential role in the development of pancreatic cancer, especially neutrophils. ANO1, AHNAK2, and ADAM9 were eventually identified as feature genes of pancreatic cancer, helping to diagnose and predict prognosis. Neural network model analysis provides us with a new idea for finding new intervention targets for pancreatic cancer.

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Order of importance of anatomical risk factors in Kienböck’s disease: An artificial neural network study

Cited by 4 publications

References 22 publications

A decreasing failure rate model with a novel approach to enhance the artificial neural network's structure for engineering and disease data analysis

A decreasing failure rate model with a novel approach to enhance the artificial neural network's structure for engineering and disease data analysis

Aseptische Lunatumnekrose: Welche sind die wichtigsten anatomischen Risikofaktoren?

A neural network model to screen feature genes for pancreatic cancer

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