Optimized Ensembled Predictive Model for Drug Toxicity
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48774-3_23
Reference23 articles.
1. Karim, A., et al.: Quantitative toxicity prediction via meta ensembling of multitask deep learning models. ACS Omega 6(18), 12306–12317 (2021)
2. Borrero, L.A., Guette, L.S., Lopez, E., Pineda, O.B., Castro, E.B.: Predicting toxicity properties through machine learning. Procedia Comput. Sci. 170, 1011–1016 (2020)
3. Zhang, L., et al.: Applications of machine learning methods in drug toxicity prediction. Curr. Top. Med. Chem. 18(12), 987–997 (2018)
4. Ali, M.M., Paul, B.K., Ahmed, K., Bui, F.M., Quinn, J.M., Moni, M.A.: Heart disease prediction using supervised machine learning algorithms: performance analysis and comparison. Comput. Biol. Med. 136, 1–10 (2021)
5. Alyasseri, Z.A.A., et al.: Review on COVID-19 diagnosis models based on machine learning and deep learning approaches. Expert. Syst. 39(3), 1–32 (2022)
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