[HTML][HTML] Ensemble transfer learning for the prediction of anti-cancer drug response
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
[PDF][PDF] Ensemble transfer learning for the prediction of anti‑cancer drug response
Y Zhu1Ε, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - scholar.archive.org
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
Ensemble transfer learning for the prediction of anti-cancer drug response
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia, M Shukla… - Scientific Reports, 2020 - osti.gov
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
Ensemble transfer learning for the prediction of anti-cancer drug response.
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - europepmc.org
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
[PDF][PDF] Ensemble transfer learning for the prediction of anti‑cancer drug response
Y Zhu1Ε, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - scienceopen.com
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
Ensemble transfer learning for the prediction of anti-cancer drug response
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - ui.adsabs.harvard.edu
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia… - arXiv preprint arXiv …, 2020 - arxiv.org
Transfer learning has been shown to be effective in many applications in which training data
for the target problem are limited but data for a related (source) problem are abundant. In …
for the target problem are limited but data for a related (source) problem are abundant. In …
[PDF][PDF] Ensemble transfer learning for the prediction of anti‑cancer drug response
Y Zhu1Ε, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - academia.edu
Methods Framework of analysis scenario. Our study involves four public in vitro drug
screening datasets, including the Cancer Therapeutics Response Portal v2 (CTRP) 3, the …
screening datasets, including the Cancer Therapeutics Response Portal v2 (CTRP) 3, the …
Ensemble transfer learning for the prediction of anti-cancer drug response.
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - search.ebscohost.com
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …
[HTML][HTML] Ensemble transfer learning for the prediction of anti-cancer drug response
Y Zhu, T Brettin, YA Evrard, A Partin, F Xia… - Scientific …, 2020 - ncbi.nlm.nih.gov
Transfer learning, which transfers patterns learned on a source dataset to a related target
dataset for constructing prediction models, has been shown effective in many applications …
dataset for constructing prediction models, has been shown effective in many applications …