PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Genomics & Informatics10.5808/gi.200762021191e10Machine learning based anti-cancer drug response prediction and search for predictor genes using cancer cell line gene expressionKexin Qiu, JoongHo Lee, HanByeol Kim, Seokhyun Yoon, Keunsoo Kanghttp://genominfo.org/upload/pdf/gi-20076.pdf, http://genominfo.org/journal/view.php?doi=10.5808/gi.20076, http://genominfo.org/upload/pdf/gi-20076.pdf
10.36227/techrxiv.132733192020Personalized drug-response prediction model for lung cancer patients using machine learningRizwan Qureshihttps://ndownloader.figshare.com/files/25562447
10.36227/techrxiv.13273319.v12020Personalized drug-response prediction model for lung cancer patients using machine learningRizwan Qureshihttps://ndownloader.figshare.com/files/25562447
Genes10.3390/genes120608442021126844kESVR: An Ensemble Model for Drug Response Prediction in Precision Medicine Using Cancer Cell Lines Gene ExpressionAbhishek Majumdar, Yueze Liu, Yaoqin Lu, Shaofeng Wu, Lijun Chenghttps://www.mdpi.com/2073-4425/12/6/844/pdf
Genes10.3390/genes1109107020201191070Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction ModelsYitan Zhu, Thomas Brettin, Yvonne A. Evrard, Fangfang Xia, Alexander Partin, Maulik Shukla, Hyunseung Yoo, James H. Doroshow, Rick L. Stevenshttps://www.mdpi.com/2073-4425/11/9/1070/pdf
IEEE Access10.1109/access.2018.2886604201974232-4238Gene Expression Analysis for Early Lung Cancer Prediction Using Machine Learning Techniques: An Eco-Genomics ApproachJayadeep Patihttp://xplorestaging.ieee.org/ielx7/6287639/8600701/08584430.pdf?arnumber=8584430
Nuclear Engineering and Technology10.1016/j.net.2022.03.01920225483027-3033Comparison and optimization of deep learning-based radiosensitivity prediction models using gene expression profiling in National Cancer Institute-60 cancer cell lineEuidam Kim, Yoonsun Chunghttps://api.elsevier.com/content/article/PII:S1738573322001395?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:S1738573322001395?httpAccept=text/plain
Proceedings of the 2017 International Conference on Computational Biology and Bioinformatics - ICCBB 201710.1145/3155077.31550782017Individual Drug Treatment Prediction in Oncology Based on Machine Learning Using Cell Culture Gene Expression DataNikolay Borisov, Victor Tkachev, Ilya Muchnik, Anton Buzdinhttp://dl.acm.org/ft_gateway.cfm?id=3155078&ftid=1935038&dwn=1
BMC Cancer10.1186/s12885-021-08359-62021211Predicting breast cancer drug response using a multiple-layer cell line drug response network modelShujun Huang, Pingzhao Hu, Ted M. Lakowskihttps://link.springer.com/content/pdf/10.1186/s12885-021-08359-6.pdf, https://link.springer.com/article/10.1186/s12885-021-08359-6/fulltext.html, https://link.springer.com/content/pdf/10.1186/s12885-021-08359-6.pdf
Computers, Materials & Continua10.32604/cmc.2022.02005520227022743-2760Drug Response Prediction of Liver Cancer Cell Line Using Deep LearningMehdi Hassan, Safdar Ali, Muhammad Sanaullah, Khuram Shahzad, Sadaf Mushtaq, Rashda Abbasi, Zulqurnain Ali, Hani Alquhayzhttps://www.techscience.com/cmc/v70n2/44673/pdf