Machine Learning for Cancer Drug Combination.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

6 citing papers in PubMed.

1. Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025
   Review
2. Leveraging high-resolution omics data for predicting responses and adverse events to immune checkpoint inhibitors.Computational and structural biotechnology journal · 2023
   Review
3. SYNPRED: prediction of drug combination effects in cancer using different synergy metrics and ensemble learning.GigaScience · 2022
   Article
4. A cross-study analysis of drug response prediction in cancer cell lines.Briefings in bioinformatics · 2022
   Article
5. Representation of molecules for drug response prediction.Briefings in bioinformatics · 2022
   Review
6. Challenge-Enabled Machine Learning to Drug-Response Prediction.The AAPS journal · 2020
   Review

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

3 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

Indexed as