AIMC Topic: Cell Line, Tumor

Clear Filters Showing 141 to 150 of 508 articles

Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.

International journal of biological macromolecules Aug 27, 2024
This study aims to develop sorafenib-loaded self-assembled nanoparticles (SFB-SANPs) using the combined approach of artificial neural network and design of experiments (ANN-DoE) and to compare it with other machine learning (ML) models. The central c...
Antineoplastic Agents Cell Line, Tumor Nanoparticles Polysaccharides Drug Liberation Particle Size Polyethyleneimine Neural Networks, Computer Drug Carriers Sorafenib Humans Machine Learning Drug Delivery Systems
View on PubMed DOI

Utilizing convolutional neural networks for discriminating cancer and stromal cells in three-dimensional cell culture images with nuclei counterstain.

Journal of biomedical optics Aug 24, 2024
SIGNIFICANCE: Accurate cell segmentation and classification in three-dimensional (3D) images are vital for studying live cell behavior and drug responses in 3D tissue culture. Evaluating diverse cell populations in 3D cell culture over time necessita...
Spheroids, Cellular Humans Cell Culture Techniques, Three Dimensional Neural Networks, Computer Neoplasms Microscopy, Confocal Fibroblasts Stromal Cells Cell Nucleus Cell Line, Tumor Imaging, Three-Dimensional Image Processing, Computer-Assisted
View on PubMed DOI

Machine learning enabled classification of lung cancer cell lines co-cultured with fibroblasts with lightweight convolutional neural network for initial diagnosis.

Journal of biomedical science Aug 23, 2024
BACKGROUND: Identification of lung cancer subtypes is critical for successful treatment in patients, especially those in advanced stages. Many advanced and personal treatments require knowledge of specific mutations, as well as up- and down-regulatio...
Carcinoma, Non-Small-Cell Lung Fibroblasts Coculture Techniques Humans Cell Line, Tumor Lung Neoplasms Neural Networks, Computer Machine Learning
View on PubMed DOI

MMFSyn: A Multimodal Deep Learning Model for Predicting Anticancer Synergistic Drug Combination Effect.

Biomolecules Aug 22, 2024
Combination therapy aims to synergistically enhance efficacy or reduce toxic side effects and has widely been used in clinical practice. However, with the rapid increase in the types of drug combinations, identifying the synergistic relationships bet...
Antineoplastic Combined Chemotherapy Protocols Drug Synergism Neoplasms Humans Antineoplastic Agents Deep Learning Cell Line, Tumor
View on PubMed DOI

Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma.

Scientific reports Aug 22, 2024
Macrophages played an important role in the progression and treatment of head and neck squamous cell carcinoma (HNSCC). We employed weighted gene co-expression network analysis (WGCNA) to identify macrophage-related genes (MRGs) and classify patients...
Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Prognosis Tumor Microenvironment Biomarkers, Tumor Immunotherapy Gene Expression Regulation, Neoplastic Male Cell Line, Tumor Humans Machine Learning Macrophages
View on PubMed DOI

is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.

Frontiers in immunology Aug 21, 2024
BACKGROUND: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the ...
DNA Ligase ATP Computational Biology Male Gene Expression Regulation, Neoplastic Middle Aged Urinary Bladder Neoplasms Humans Protein Interaction Maps Female Gene Expression Profiling Cell Line, Tumor Machine Learning Aged Gene Regulatory Networks Single-Cell Analysis Prognosis Biomarkers, Tumor
View on PubMed DOI

Machine learning analysis of oxidative stress-related phenotypes for specific gene screening in ovarian cancer.

Environmental toxicology Aug 20, 2024
BACKGROUND: Oxidative stress serves a crucial role in tumor development. However, the relationship between ovarian cancer and oxidative stress remains unknown. We aimed to create an oxidative stress-related prognostic signature to enhance the prognos...
Machine Learning Phenotype Prognosis Female Humans Oxidative Stress Gene Expression Regulation, Neoplastic Ovarian Neoplasms Genetic Testing Biomarkers, Tumor Middle Aged Cell Line, Tumor
View on PubMed DOI

Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines.

ACS applied materials & interfaces Aug 20, 2024
Mechanobiological measurements have the potential to discriminate healthy cells from pathological cells. However, a technology frequently used to measure these properties, i.e., atomic force microscopy (AFM), suffers from its low output and lack of s...
Cell Line, Tumor Humans Machine Learning Algorithms Fuzzy Logic Microscopy, Atomic Force
View on PubMed DOI

Identification and analysis of significant genes in nonalcoholic steatohepatitis-hepatocellular carcinoma transformation: Bioinformatics analysis and machine learning approach.

Molecular immunology Aug 13, 2024
PURPOSE: Nonalcoholic steatohepatitis (NASH) has been an increasingly significant contributor to hepatocellular carcinoma (HCC). Understanding the progression from NASH to HCC is critical to early diagnosis and elucidating the underlying mechanisms.
Non-alcoholic Fatty Liver Disease Cell Transformation, Neoplastic Suppressor of Cytokine Signaling Proteins Single-Cell Analysis Computational Biology Gene Expression Regulation, Neoplastic Humans Machine Learning Prognosis Liver Neoplasms Carcinoma, Hepatocellular Disease Progression Cell Line, Tumor
View on PubMed DOI

Accurate Identification of Cancer Cells in Complex Pre-Clinical Models Using a Deep-Learning Neural Network: A Transfection-Free Approach.

Advanced biology Aug 12, 2024
3D co-cultures are key tools for in vitro biomedical research as they recapitulate more closely the in vivo environment while allowing a tighter control on the culture's composition and experimental conditions. The limited technologies available for ...
Humans Deep Learning Cell Line, Tumor Ovarian Neoplasms Coculture Techniques Neural Networks, Computer Female Reproducibility of Results
View on PubMed DOI
Popular Topics
Recent Journals