8 citations · 11 across the 3 of their papers we have counts for
3 papers
q-bio.QM2025★ 2 cited
Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
Yepeng Huang, Xiaorui Su, Varun Ullanat +10
Predicting clinical outcomes from preclinical data is essential for selecting safe and effective drug combinations and for reducing late-stage failures. AI models use molecular str…
cs.CL2022★ 1 cited
PHEE: A Dataset for Pharmacovigilance Event Extraction from Text
Zhaoyue Sun, Jiazheng Li, Gabriele Pergola +5
The primary goal of drug safety researchers and regulators is to promptly identify adverse drug reactions. Doing so may in turn prevent or reduce the harm to patients and ultimatel…
cs.LG2022★ 8 cited
Interpretable bilinear attention network with domain adaptation improves drug-target prediction
Peizhen Bai, Filip Miljković, Bino John +1
Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model a…