Editorial: Deep Learning for Toxicity and Disease Prediction.
作者信息
Gong Ping, Zhang Chaoyang, Chen Minjun
机构信息
Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, MS, United States.
School of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, United States.
出版信息
Front Genet. 2020 Feb 26;11:175. doi: 10.3389/fgene.2020.00175. eCollection 2020.
Abstract
摘要
相似文献
1
Editorial: Deep Learning for Toxicity and Disease Prediction.
Front Genet. 2020 Feb 26;11:175. doi: 10.3389/fgene.2020.00175. eCollection 2020.
2
Deep learning for predicting toxicity of chemicals: a mini review.
J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2018;36(4):252-271. doi: 10.1080/10590501.2018.1537563. Epub 2019 Mar 1.
3
Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT.
Med Phys. 2018 Oct;45(10):4763-4774. doi: 10.1002/mp.13122. Epub 2018 Sep 10.
4
Deep learning for computational chemistry.
J Comput Chem. 2017 Jun 15;38(16):1291-1307. doi: 10.1002/jcc.24764. Epub 2017 Mar 8.
5
tRNA-DL: A Deep Learning Approach to Improve tRNAscan-SE Prediction Results.
Hum Hered. 2018;83(3):163-172. doi: 10.1159/000493215. Epub 2019 Jan 25.
6
Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.
JAMA Netw Open. 2019 Jan 4;2(1):e186937. doi: 10.1001/jamanetworkopen.2018.6937.
7
Toxicity Prediction Method Based on Multi-Channel Convolutional Neural Network.
Molecules. 2019 Sep 17;24(18):3383. doi: 10.3390/molecules24183383.
8
Deep learning methods for protein torsion angle prediction.
BMC Bioinformatics. 2017 Sep 18;18(1):417. doi: 10.1186/s12859-017-1834-2.
9
Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.
Artif Intell Med. 2019 Jul;98:59-76. doi: 10.1016/j.artmed.2019.07.008. Epub 2019 Jul 25.
10
Effects of Food Contamination on Gastrointestinal Morbidity: Comparison of Different Machine-Learning Methods.
Int J Environ Res Public Health. 2019 Mar 7;16(5):838. doi: 10.3390/ijerph16050838.
引用本文的文献
1
Accurate Prediction of Epigenetic Multi-Targets with Graph Neural Network-Based Feature Extraction.
Int J Mol Sci. 2022 Nov 1;23(21):13347. doi: 10.3390/ijms232113347.
本文引用的文献
1
Current status and future trends of clinical diagnoses via image-based deep learning.
Theranostics. 2019 Oct 12;9(25):7556-7565. doi: 10.7150/thno.38065. eCollection 2019.
2
Quantitative structure-activity relationship analysis using deep learning based on a novel molecular image input technique.
Bioorg Med Chem Lett. 2018 Nov 1;28(20):3400-3403. doi: 10.1016/j.bmcl.2018.08.032. Epub 2018 Aug 27.
3
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL.
Chem Sci. 2018 Jun 6;9(24):5441-5451. doi: 10.1039/c8sc00148k. eCollection 2018 Jun 28.
4
A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition.
Sensors (Basel). 2017 Sep 4;17(9):2022. doi: 10.3390/s17092022.
5
Deep Learning Driven Visual Path Prediction From a Single Image.
IEEE Trans Image Process. 2016 Dec;25(12):5892-5904. doi: 10.1109/TIP.2016.2613686. Epub 2016 Sep 26.
6
Deep Learning in Drug Discovery.
Mol Inform. 2016 Jan;35(1):3-14. doi: 10.1002/minf.201501008. Epub 2015 Dec 30.
7
Deep learning for computational biology.
Mol Syst Biol. 2016 Jul 29;12(7):878. doi: 10.15252/msb.20156651.
8
Deep learning.
Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539.
9
A logical calculus of the ideas immanent in nervous activity. 1943.
Bull Math Biol. 1990;52(1-2):99-115; discussion 73-97.
Zotero 插件