181 related articles for article (PubMed ID: 36685926)
21. Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction.
Myung Y; de Sá AGC; Ascher DB
Nucleic Acids Res; 2024 Apr; ():. PubMed ID: 38634808
[TBL] [Abstract][Full Text] [Related]
22. Application of random forest based on semi-automatic parameter adjustment for optimization of anti-breast cancer drugs.
Liu J; Zhou Z; Kong S; Ma Z
Front Oncol; 2022; 12():956705. PubMed ID: 35936743
[TBL] [Abstract][Full Text] [Related]
23. ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches.
Sharma AK; Srivastava GN; Roy A; Sharma VK
Front Pharmacol; 2017; 8():880. PubMed ID: 29249969
[TBL] [Abstract][Full Text] [Related]
24. Pre-processing feature selection for improved C&RT models for oral absorption.
Newby D; Freitas AA; Ghafourian T
J Chem Inf Model; 2013 Oct; 53(10):2730-42. PubMed ID: 24050619
[TBL] [Abstract][Full Text] [Related]
25. Performance Evaluation of Regression Models for the Prediction of the COVID-19 Reproduction Rate.
Kaliappan J; Srinivasan K; Mian Qaisar S; Sundararajan K; Chang CY; C S
Front Public Health; 2021; 9():729795. PubMed ID: 34595149
[TBL] [Abstract][Full Text] [Related]
26. A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.
Paulose R; Jegatheesan K; Balakrishnan GS
Indian J Pharmacol; 2018; 50(4):169-176. PubMed ID: 30505052
[TBL] [Abstract][Full Text] [Related]
27. A two-stage modeling approach for breast cancer survivability prediction.
Sedighi-Maman Z; Mondello A
Int J Med Inform; 2021 May; 149():104438. PubMed ID: 33730681
[TBL] [Abstract][Full Text] [Related]
28. Predicting Organ Toxicity Using in Vitro Bioactivity Data and Chemical Structure.
Liu J; Patlewicz G; Williams AJ; Thomas RS; Shah I
Chem Res Toxicol; 2017 Nov; 30(11):2046-2059. PubMed ID: 28768096
[TBL] [Abstract][Full Text] [Related]
29. Consultation length and no-show prediction for improving appointment scheduling efficiency at a cardiology clinic: A data analytics approach.
Srinivas S; Salah H
Int J Med Inform; 2021 Jan; 145():104290. PubMed ID: 33099184
[TBL] [Abstract][Full Text] [Related]
30. Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [
Gómez OV; Herraiz JL; Udías JM; Haug A; Papp L; Cioni D; Neri E
Cancers (Basel); 2022 Jun; 14(12):. PubMed ID: 35740588
[TBL] [Abstract][Full Text] [Related]
31. Computer-aided drug design and virtual screening of targeted combinatorial libraries of mixed-ligand transition metal complexes of 2-butanone thiosemicarbazone.
Khan T; Ahmad R; Azad I; Raza S; Joshi S; Khan AR
Comput Biol Chem; 2018 Aug; 75():178-195. PubMed ID: 29883916
[TBL] [Abstract][Full Text] [Related]
32. Construction of An Oral Bioavailability Prediction Model Based on Machine Learning for Evaluating Molecular Modifications.
Yang Q; Fan L; Hao E; Hou X; Deng J; Xia Z; Du Z
J Pharm Sci; 2024 May; 113(5):1155-1167. PubMed ID: 38430955
[TBL] [Abstract][Full Text] [Related]
33. A Machine Learning-Based QSAR Model for Benzimidazole Derivatives as Corrosion Inhibitors by Incorporating Comprehensive Feature Selection.
Liu Y; Guo Y; Wu W; Xiong Y; Sun C; Yuan L; Li M
Interdiscip Sci; 2019 Dec; 11(4):738-747. PubMed ID: 31486019
[TBL] [Abstract][Full Text] [Related]
34. Predicting Dose-Range Chemical Toxicity using Novel Hybrid Deep Machine-Learning Method.
Limbu S; Zakka C; Dakshanamurthy S
Toxics; 2022 Nov; 10(11):. PubMed ID: 36422913
[TBL] [Abstract][Full Text] [Related]
35. In silico prediction of major drug clearance pathways by support vector machines with feature-selected descriptors.
Toshimoto K; Wakayama N; Kusama M; Maeda K; Sugiyama Y; Akiyama Y
Drug Metab Dispos; 2014 Nov; 42(11):1811-9. PubMed ID: 25128502
[TBL] [Abstract][Full Text] [Related]
36. Interpretable-ADMET: a web service for ADMET prediction and optimization based on deep neural representation.
Wei Y; Li S; Li Z; Wan Z; Lin J
Bioinformatics; 2022 May; 38(10):2863-2871. PubMed ID: 35561160
[TBL] [Abstract][Full Text] [Related]
37. Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.
Kumar R; Sharma A; Siddiqui MH; Tiwari RK
Mini Rev Med Chem; 2018; 18(3):196-207. PubMed ID: 28302041
[TBL] [Abstract][Full Text] [Related]
38. Machine learning models in breast cancer survival prediction.
Montazeri M; Montazeri M; Montazeri M; Beigzadeh A
Technol Health Care; 2016; 24(1):31-42. PubMed ID: 26409558
[TBL] [Abstract][Full Text] [Related]
39. ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning.
Jiang D; Lei T; Wang Z; Shen C; Cao D; Hou T
J Cheminform; 2020 Mar; 12(1):16. PubMed ID: 33430990
[TBL] [Abstract][Full Text] [Related]
40. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.
Murat M; Chang SW; Abu A; Yap HJ; Yong KT
PeerJ; 2017; 5():e3792. PubMed ID: 28924506
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
