logo
ResearchBunny Logo
An integrated network representation of multiple cancer-specific data for graph-based machine learning

Medicine and Health

An integrated network representation of multiple cancer-specific data for graph-based machine learning

L. Pu, M. Singha, et al.

This innovative research conducted by Limeng Pu, Manali Singha, Hsiao-Chun Wu, Costas Busch, J. Ramanujam, and Michal Brylinski unveils a breakthrough in predicting cancer cell line responses to drug treatments using genomic data. By leveraging a unique graph reduction algorithm, the study enhances prediction accuracy through advanced feature representation, showcasing the power of non-Euclidean data in cancer pharmacotherapy.

00:00
Playback language: English
Citation Metrics
Citations
0
Influential Citations
0
Reference Count
0

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

Related Publications

Explore these studies to deepen your understanding of the subject.

UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120)
Medicine and Health

UroPredict: Machine learning model on real-world data for prediction of kidney cancer recurrence (UroCCR-120)

G. Margue, L. Ferrer, et al.

Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections
Medicine and Health

Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections

J. Yang, D. W. Eyre, et al.

Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
Computer Science

Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing

D. Rankin, M. Black, et al.

Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals
Engineering and Technology

Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals

S. W. Rabkin, A. Cataldo, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny