A two-stage feature selection approach using hybrid quasi-opposition self-adaptive coati optimization algorithm for breast cancer classification
K Thirumoorthy - Applied Soft Computing, 2023 - Elsevier
Breast cancer (BC) is one of the leading causes of high mortality rates among women. An
early disease diagnosis is crucial in breast cancer's treatment for improving the survival rate …
early disease diagnosis is crucial in breast cancer's treatment for improving the survival rate …
Advancing Peptide-Based Cancer Therapy with AI: In-Depth Analysis of State-of-the-Art AI Models
Anticancer peptides (ACPs) play a vital role in selectively targeting and eliminating cancer
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …
cells. Evaluating and comparing predictions from various machine learning (ML) and deep …
Identification of a Novel eight-gene risk model for Predicting Survival in Glioblastoma: a Comprehensive Bioinformatic Analysis
Simple Summary People with glioblastoma (GBM) universally have poor survival despite
undergoing aggressive treatments. In this study, we aimed to determine genetic biomarkers …
undergoing aggressive treatments. In this study, we aimed to determine genetic biomarkers …
Molecular cluster mining of adrenocortical carcinoma via multi-omics data analysis aids precise clinical therapy
Y Guan, S Yue, Y Chen, Y Pan, L An, H Du, C Liang - Cells, 2022 - mdpi.com
Adrenocortical carcinoma (ACC) is a malignancy of the endocrine system. We collected
clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA …
clinical and pathological features, genomic mutations, DNA methylation profiles, and mRNA …
ExhauFS: exhaustive search-based feature selection for classification and survival regression
Feature selection is one of the main techniques used to prevent overfitting in machine
learning applications. The most straightforward approach for feature selection is an …
learning applications. The most straightforward approach for feature selection is an …
Graph based feature selection for reduction of dimensionality in next-generation rna sequencing datasets
Analysis of high-dimensional data, with more features (p) than observations (N)(p> N),
places significant demand in cost and memory computational usage attributes. Feature …
places significant demand in cost and memory computational usage attributes. Feature …
AITeQ: a machine learning framework for Alzheimer's prediction using a distinctive five-gene signature
Neurodegenerative diseases, such as Alzheimer's disease, pose a significant global health
challenge with their complex etiology and elusive biomarkers. In this study, we developed …
challenge with their complex etiology and elusive biomarkers. In this study, we developed …
Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis
JY Park, JW Lee, M Park - BioData Mining, 2023 - Springer
Background Cancer subtype identification is important for the early diagnosis of cancer and
the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient …
the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient …
Performance and clinical utility of a new supervised machine-learning pipeline in detecting rare ciliopathy patients based on deep phenotyping from electronic health …
C Faviez, M Vincent, N Garcelon, O Boyer… - Orphanet Journal of …, 2024 - Springer
Background Rare diseases affect approximately 400 million people worldwide. Many of
them suffer from delayed diagnosis. Among them, NPHP1-related renal ciliopathies need to …
them suffer from delayed diagnosis. Among them, NPHP1-related renal ciliopathies need to …
The Role of DNA Microarrays and Machine Learning in Cancer Research: Profiling Gene Expression for Diagnosis and Treatment
This chapter explores the pivotal intersection of DNA microarrays and machine learning
within the area of cancer research. It underscores the principal significance of gene …
within the area of cancer research. It underscores the principal significance of gene …