AIMC Topic: Drug Resistance, Neoplasm

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Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.

Biomedical engineering online
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
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
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)
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
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
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...

Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.

Briefings in bioinformatics
The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a cr...

Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance.

Briefings in bioinformatics
Although chemotherapy is the first-line treatment for ovarian cancer (OCa) patients, chemoresistance (CR) decreases their progression-free survival. This paper investigates the genetic interaction (GI) related to OCa-CR. To decrease the complexity of...