AIMC Topic: Biomarkers, Tumor

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Machine Learning-Based Detection of Bladder Cancer by Urine cfDNA Fragmentation Hotspots that Capture Cancer-Associated Molecular Features.

Clinical chemistry Dec 2, 2024
BACKGROUND: cfDNA fragmentomics-based liquid biopsy is a potential option for noninvasive bladder cancer (BLCA) detection that remains an unmet clinical need.
Humans Machine Learning Middle Aged Urinary Bladder Neoplasms Cell-Free Nucleic Acids Liquid Biopsy Female Aged Biomarkers, Tumor Male
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[Screening of characteristic genes of salivary gland adenoid cystic carcinoma based on weighted co-expression network and machine learning].

Shanghai kou qiang yi xue = Shanghai journal of stomatology Dec 1, 2024
PURPOSE: To identify potential biomarkers of salivary gland adenoid cystic carcinoma to further understand the potential pathogenesis of adenoid cystic carcinoma.
Humans Machine Learning Biomarkers, Tumor Gene Expression Profiling RNA, Long Noncoding ROC Curve Salivary Gland Neoplasms Gene Regulatory Networks Carcinoma, Adenoid Cystic Gene Expression Regulation, Neoplastic
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Deciphering the Role of SLFN12: A Novel Biomarker for Predicting Immunotherapy Outcomes in Glioma Patients Through Artificial Intelligence.

Journal of cellular and molecular medicine Dec 1, 2024
Gliomas are the most prevalent form of primary brain tumours. Recently, targeting the PD-1 pathway with immunotherapies has shown promise as a novel glioma treatment. However, not all patients experience long-lasting benefits, underscoring the necess...
Programmed Cell Death 1 Receptor Humans Artificial Intelligence Gene Expression Regulation, Neoplastic Biomarkers, Tumor Prognosis Cell Proliferation Tumor Microenvironment Brain Neoplasms Treatment Outcome Cell Line, Tumor Glioma Immunotherapy
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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT-Based Radiomic Features in Non-Small Cell Lung Cancer.

Cancer medicine Dec 1, 2024
BACKGROUND: Non-small-cell lung cancer (NSCLC) remains a global health challenge, driving morbidity and mortality. The emerging field of radiogenomics utilizes statistical methods to correlate radiographic tumor features with genomic characteristics ...
Carcinoma, Non-Small-Cell Lung Radiomics Biomarkers, Tumor Male Middle Aged Gene Expression Profiling Lung Neoplasms Gene Expression Regulation, Neoplastic Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Machine Learning
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Building a Risk Scoring Model for ARDS in Lung Adenocarcinoma Patients Using Machine Learning Algorithms.

Journal of cellular and molecular medicine Dec 1, 2024
Lung adenocarcinoma (LUAD), the predominant form of non-small-cell lung cancer, is frequently complicated by acute respiratory distress syndrome (ARDS), which increases mortality risks. Investigating the prognostic implications of ARDS-related genes ...
Algorithms Prognosis Female Risk Factors Humans Machine Learning Gene Expression Profiling Lung Neoplasms Gene Expression Regulation, Neoplastic Respiratory Distress Syndrome Biomarkers, Tumor Male Risk Assessment DNA Copy Number Variations Mutation Adenocarcinoma of Lung
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GD-Net: An Integrated Multimodal Information Model Based on Deep Learning for Cancer Outcome Prediction and Informative Feature Selection.

Journal of cellular and molecular medicine Dec 1, 2024
Multimodal information provides valuable resources for cancer prognosis and survival prediction. However, the computational integration of this heterogeneous data information poses significant challenges due to the complex interactions between molecu...
Neoplasms Deep Learning Liver Neoplasms Computational Biology Gene Expression Regulation, Neoplastic DNA Methylation MicroRNAs Humans Algorithms Prognosis Biomarkers, Tumor
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DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways.

Cancer research communications Dec 1, 2024
DeePathNet integrates cancer-specific biological pathways using transformer-based deep learning for enhanced cancer analysis. It outperforms existing models in predicting drug responses, cancer types, and subtypes. By enabling pathway-level biomarker...
Deep Learning Computational Biology Humans Biomarkers, Tumor Neoplasms
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Dual-stage optimizer for systematic overestimation adjustment applied to multi-objective genetic algorithms for biomarker selection.

Briefings in bioinformatics Nov 22, 2024
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test va...
Humans Machine Learning Biomarkers, Tumor Algorithms Neoplasms Computational Biology
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Comprehensive bioinformatics and machine learning analyses for breast cancer staging using TCGA dataset.

Briefings in bioinformatics Nov 22, 2024
Breast cancer is an alarming global health concern, including a vast and varied set of illnesses with different molecular characteristics. The fusion of sophisticated computational methodologies with extensive biological datasets has emerged as an ef...
Humans Breast Neoplasms Biomarkers, Tumor Gene Expression Profiling Computational Biology Neoplasm Staging Machine Learning Gene Expression Regulation, Neoplastic Algorithms Databases, Genetic Female MicroRNAs
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Hepatocellular Carcinoma Immune Microenvironment Analysis: A Comprehensive Assessment with Computational and Classical Pathology.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 15, 2024
PURPOSE: The spatial variability and clinical relevance of the tumor immune microenvironment (TIME) are still poorly understood for hepatocellular carcinoma (HCC). In this study, we aim to develop a deep learning (DL)-based image analysis model for t...
Computational Biology Lymphocytes, Tumor-Infiltrating Immunophenotyping Humans Immunohistochemistry Algorithms Liver Neoplasms Prognosis Carcinoma, Hepatocellular Image Processing, Computer-Assisted Biomarkers, Tumor Female Male Aged Middle Aged Tumor Microenvironment Deep Learning
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