These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

303 related articles for article (PubMed ID: 30320286)

  • 1. Prediction of Compound Profiling Matrices, Part II: Relative Performance of Multitask Deep Learning and Random Forest Classification on the Basis of Varying Amounts of Training Data.
    Rodríguez-Pérez R; Bajorath J
    ACS Omega; 2018 Sep; 3(9):12033-12040. PubMed ID: 30320286
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Evaluation of multi-target deep neural network models for compound potency prediction under increasingly challenging test conditions.
    Rodríguez-Pérez R; Bajorath J
    J Comput Aided Mol Des; 2021 Mar; 35(3):285-295. PubMed ID: 33598870
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.
    Xu Y; Ma J; Liaw A; Sheridan RP; Svetnik V
    J Chem Inf Model; 2017 Oct; 57(10):2490-2504. PubMed ID: 28872869
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of Human Cytochrome P450 Inhibition Using a Multitask Deep Autoencoder Neural Network.
    Li X; Xu Y; Lai L; Pei J
    Mol Pharm; 2018 Oct; 15(10):4336-4345. PubMed ID: 29775322
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Data Sets.
    Wenzel J; Matter H; Schmidt F
    J Chem Inf Model; 2019 Mar; 59(3):1253-1268. PubMed ID: 30615828
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Developing and comparing deep learning and machine learning algorithms for osteoporosis risk prediction.
    Qiu C; Su K; Luo Z; Tian Q; Zhao L; Wu L; Deng H; Shen H
    Front Artif Intell; 2024; 7():1355287. PubMed ID: 38919268
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Spatial Assessment of Solar Radiation by Machine Learning and Deep Neural Network Models Using Data Provided by the COMS MI Geostationary Satellite: A Case Study in South Korea.
    Yeom JM; Park S; Chae T; Kim JY; Lee CS
    Sensors (Basel); 2019 May; 19(9):. PubMed ID: 31060305
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting drug-target interaction network using deep learning model.
    You J; McLeod RD; Hu P
    Comput Biol Chem; 2019 Jun; 80():90-101. PubMed ID: 30939415
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Autoencoder and restricted Boltzmann machine for transfer learning in functional magnetic resonance imaging task classification.
    Hwang J; Lustig N; Jung M; Lee JH
    Heliyon; 2023 Jul; 9(7):e18086. PubMed ID: 37519689
    [TBL] [Abstract][Full Text] [Related]  

  • 10. DNN-Dom: predicting protein domain boundary from sequence alone by deep neural network.
    Shi Q; Chen W; Huang S; Jin F; Dong Y; Wang Y; Xue Z
    Bioinformatics; 2019 Dec; 35(24):5128-5136. PubMed ID: 31197306
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Forecasting actual evapotranspiration without climate data based on stacked integration of DNN and meta-heuristic models across China from 1958 to 2021.
    Elbeltagi A; Srivastava A; Li P; Jiang J; Jinsong D; Rajput J; Khadke L; Awad A
    J Environ Manage; 2023 Nov; 345():118697. PubMed ID: 37688967
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Assessing Deep and Shallow Learning Methods for Quantitative Prediction of Acute Chemical Toxicity.
    Liu R; Madore M; Glover KP; Feasel MG; Wallqvist A
    Toxicol Sci; 2018 Aug; 164(2):512-526. PubMed ID: 29722883
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data.
    Koutsoukas A; Monaghan KJ; Li X; Huan J
    J Cheminform; 2017 Jun; 9(1):42. PubMed ID: 29086090
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Neural Network Models for Predicting Chemically Induced Liver Toxicity Endpoints From Transcriptomic Responses.
    Wang H; Liu R; Schyman P; Wallqvist A
    Front Pharmacol; 2019; 10():42. PubMed ID: 30804783
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of Compound Profiling Matrices Using Machine Learning.
    Rodríguez-Pérez R; Miyao T; Jasial S; Vogt M; Bajorath J
    ACS Omega; 2018 Apr; 3(4):4713-4723. PubMed ID: 30023899
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Effect of missing data on multitask prediction methods.
    de la Vega de León A; Chen B; Gillet VJ
    J Cheminform; 2018 May; 10(1):26. PubMed ID: 29789977
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A deep neural network-based approach for prediction of mutagenicity of compounds.
    Kumar R; Khan FU; Sharma A; Siddiqui MH; Aziz IB; Kamal MA; Ashraf GM; Alghamdi BS; Uddin MS
    Environ Sci Pollut Res Int; 2021 Sep; 28(34):47641-47650. PubMed ID: 33895950
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep neural network-based prediction of tsunami wave attenuation by mangrove forests.
    Adytia D; Tarwidi D; Saepudin D; Husrin S; Kasim ARM; Romlie MF; Samsudin D
    MethodsX; 2024 Dec; 13():102791. PubMed ID: 38975289
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Fuzzy Clustering-Based Deep Learning for Short-Term Load Forecasting in Power Grid Systems Using Time-Varying and Time-Invariant Features.
    Chan KY; Yiu KFC; Kim D; Abu-Siada A
    Sensors (Basel); 2024 Feb; 24(5):. PubMed ID: 38474927
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Deep Neural Networks for Multicomponent Molecular Systems.
    Hanaoka K
    ACS Omega; 2020 Aug; 5(33):21042-21053. PubMed ID: 32875241
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.