Advances in Machine Learning Processing of Big Data from Disease Diagnosis Sensors
S Lu, J Yang, Y Gu, D He, H Wu, W Sun, D Xu, C Li… - ACS …, 2024 - ACS Publications
Exploring accurate, noninvasive, and inexpensive disease diagnostic sensors is a critical
task in the fields of chemistry, biology, and medicine. The complexity of biological systems …
task in the fields of chemistry, biology, and medicine. The complexity of biological systems …
A hybrid machine learning feature selection model—HMLFSM to enhance gene classification applied to multiple colon cancers dataset
Colon cancer is a significant global health problem, and early detection is critical for
improving survival rates. Traditional detection methods, such as colonoscopies, can be …
improving survival rates. Traditional detection methods, such as colonoscopies, can be …
p53 regulates expression of nuclear envelope components in cancer cells
Nuclear organisation and architecture are essential for the maintenance of genomic integrity
as well as for the epigenetic regulations and gene expression. Disruption of lamin B1, major …
as well as for the epigenetic regulations and gene expression. Disruption of lamin B1, major …
Sustaining accurate detection of phishing URLs using SDN and feature selection approaches
Phishing is an online fraud that deceives visitors by impersonating a legitimate website to
steal their confidential or personal information. This is a well-known form of cybercrime. With …
steal their confidential or personal information. This is a well-known form of cybercrime. With …
Alpha-actnin-4 (ACTN4) selectively affects the DNA double-strand breaks repair in non-small lung carcinoma cells
D Kriger, K Novitskaya, G Vasileva, E Lomert… - Biology Direct, 2022 - Springer
Background ACTN4 is an actin-binding protein involved in many cellular processes,
including cancer development. High ACTN4 expression is often associated with a poor …
including cancer development. High ACTN4 expression is often associated with a poor …
A comparison of single imputation and multiple imputation methods for missing data in different oncogene expression profiles
W Ye, L Zhang, W Zhang, X Wu, D Yi… - Biostatistics & …, 2022 - Taylor & Francis
To evaluate the effects of multiple-imputation (MI) method for missing data in gene
expression profiles with different datasets and percentages of missing values compared with …
expression profiles with different datasets and percentages of missing values compared with …
CT Radiomics-Based Nomogram for Predicting the Lateral Neck Lymph Node Metastasis in Papillary Thyroid Carcinoma: A Prospective Multicenter Study
L Dong, X Han, P Yu, W Zhang, C Wang, Q Sun… - Academic …, 2023 - Elsevier
Rationale and Objectives This study is based on multicenter cohorts and aims to utilize
computed tomography (CT) images to construct a radiomics nomogram for predicting the …
computed tomography (CT) images to construct a radiomics nomogram for predicting the …
A hybrid improved multi-objective particle swarm optimization feature selection algorithm for high-dimensional small sample data
X Pan, J Sun, Y Xue - … Conference on Natural Computation, Fuzzy Systems …, 2022 - Springer
Traditional feature selection methods have great limitations for processing high-dimensional
small sample data, and it is difficult to accurately and efficiently propose the optimal feature …
small sample data, and it is difficult to accurately and efficiently propose the optimal feature …
Scoping Review: Application of Machine Learning Techniques in Genetic Diagnosis
B Faria, M Ribeiro, R Simões, S Valente… - World Conference on …, 2023 - Springer
Abstract Machine learning techniques have been an important support for disease
prediction and diagnosis utilizing genetic variants classification. This scoping review aimed …
prediction and diagnosis utilizing genetic variants classification. This scoping review aimed …