AIMC Topic: Drug Resistance, Neoplasm
Clear Filters Showing 71 to 80 of 94 articles
AGCLNDA: Enhancing the Prediction of ncRNA-Drug Resistance Association Using Adaptive Graph Contrastive Learning.
IEEE journal of biomedical and health informatics
Jun 1, 2025
Non-coding RNAs (ncRNAs), which do not encode proteins, have been implicated in chemotherapy resistance in cancer treatment. Given the high costs and time requirements of traditional biological experiments, there is an increasing need for computation...
Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.
Scientific reports
May 31, 2025
Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice h...
Integrating Bulk and Single-Cell Transcriptomics with Machine Learning Reveals a Heme Metabolism-Based Panel for Lung Adenocarcinoma Chemotherapy Resistance.
International journal of molecular sciences
May 14, 2025
Lung adenocarcinoma (LUAD) is a leading cause of cancer-related mortality, with heme metabolism playing a critical role in tumor progression and treatment resistance. This study investigates the clinical implications of heme metabolism in LUAD, focus...
Heme
Drug Resistance, Neoplasm
Adenocarcinoma of Lung
Multidrug Resistance-Associated Proteins
Lung Neoplasms
Gene Expression Regulation, Neoplastic
Ferroptosis
Cisplatin
Machine Learning
Multidrug Resistance-Associated Protein 2
Gene Expression Profiling
Humans
Prognosis
Transcriptome
Female
Cell Line, Tumor
Antineoplastic Agents
Single-Cell Analysis
Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.
Biomedical engineering online
May 13, 2025
BACKGROUND: The study aimed at developing and validating a deep learning (DL) model based on the ultrasound imaging for predicting the platinum resistance of patients with epithelial ovarian cancer (EOC).
A quantitative characterization of the heterogeneous response of glioblastoma U-87 MG cell line to temozolomide.
Scientific reports
May 8, 2025
Most cancers are genetically and phenotypically heterogeneous. This includes subpopulations of cells with different levels of sensitivity to chemotherapy, which may lead to treatment failure as the more resistant cells can survive drug treatment and ...
Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.
Journal of cellular and molecular medicine
Jan 1, 2025
Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and developing mitophagy-based treatments to combat drug resistance remains challenging. Herein, BayeDEM (...
Multi-task deep latent spaces for cancer survival and drug sensitivity prediction.
Bioinformatics (Oxford, England)
Sep 1, 2024
MOTIVATION: Cancer is a very heterogeneous disease that can be difficult to treat without addressing the specific mechanisms driving tumour progression in a given patient. High-throughput screening and sequencing data from cancer cell-lines has drive...
Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.
Briefings in bioinformatics
Jul 25, 2024
With the ever-increasing number of artificial intelligence (AI) systems, mitigating risks associated with their use has become one of the most urgent scientific and societal issues. To this end, the European Union passed the EU AI Act, proposing solu...
How Artificial Intelligence Unravels the Complex Web of Cancer Drug Response.
Cancer research
Jun 4, 2024
The intersection of precision medicine and artificial intelligence (AI) holds profound implications for cancer treatment, with the potential to significantly advance our understanding of drug responses based on the intricate architecture of tumor cel...
Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer.
Cancer research
Apr 14, 2023
UNLABELLED: Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying mol...
Gene Regulatory Networks
Proto-Oncogene Proteins c-myb
Machine Learning
Bayes Theorem
Humans
Computer Simulation
Basic Helix-Loop-Helix Leucine Zipper Transcription Factors
Male
Androstenes
Prostatic Neoplasms
Drug Resistance, Neoplasm
Gene Expression Profiling
Transcription, Genetic
Repressor Proteins
Proto-Oncogene Proteins c-ets
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