April 4, 2024, 4:41 a.m. | Fatemeh Abbasi, Juho Rousu

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.02484v1 Announce Type: new
Abstract: In this mini-review, we explore the new prediction methods for drug combination synergy relying on high-throughput combinatorial screens. The fast progress of the field is witnessed in the more than thirty original machine learning methods published since 2021, a clear majority of them based on deep learning techniques. We aim to put these papers under a unifying lens by highlighting the core technologies, the data sources, the input data types and synergy scores used in …

abstract arxiv clear combination cs.ai cs.lg deep learning deep learning techniques explore machine machine learning prediction progress q-bio.qm review synergy them type

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Alternance DATA/AI Engineer (H/F)

@ SQLI | Le Grand-Quevilly, France