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 *

148 related articles for article (PubMed ID: 39351774)

  • 1. Predictive Modeling of High-Entropy Alloys and Amorphous Metallic Alloys Using Machine Learning.
    Jung SG; Jung G; Cole JM
    J Chem Inf Model; 2024 Oct; 64(19):7313-7336. PubMed ID: 39351774
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic Prediction of Band Gaps of Inorganic Materials Using a Gradient Boosted and Statistical Feature Selection Workflow.
    Jung SG; Jung G; Cole JM
    J Chem Inf Model; 2024 Feb; 64(4):1187-1200. PubMed ID: 38320103
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning-guided exploration and experimental assessment of unreported compositions in the quaternary Ti-Zr-Cu-Pd biocompatible metallic glass system.
    Douest Y; Forrest RM; Ter-Ovanessian B; Courtois N; Tancret F; Greer AL; Chevalier J; Fabrègue D
    Acta Biomater; 2024 Feb; 175():411-421. PubMed ID: 38135205
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Phase Prediction Study of High-Entropy Energy Alloy Generation Based on Machine Learning.
    He Z; Zhang H
    Comput Intell Neurosci; 2022; 2022():8904341. PubMed ID: 35707197
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Combining Machine Learning and Molecular Dynamics to Predict Mechanical Properties and Microstructural Evolution of FeNiCrCoCu High-Entropy Alloys.
    Yu J; Yu F; Fu Q; Zhao G; Gong C; Wang M; Zhang Q
    Nanomaterials (Basel); 2023 Mar; 13(6):. PubMed ID: 36985862
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine-Learning Prediction of Curie Temperature from Chemical Compositions of Ferromagnetic Materials.
    Jung SG; Jung G; Cole JM
    J Chem Inf Model; 2024 Aug; 64(16):6388-6409. PubMed ID: 39110635
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting Yield Strength and Plastic Elongation in Body-Centered Cubic High-Entropy Alloys.
    Ibarra Hoyos D; Simmons Q; Poon J
    Materials (Basel); 2024 Sep; 17(17):. PubMed ID: 39274811
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine Learning-Based Design of Superhard High-Entropy Nitride Coatings.
    Zhang X; Jia B; Zeng Z; Zeng X; Wan Q; Pogrebnjak A; Zhang J; Pelenovich V; Yang B
    ACS Appl Mater Interfaces; 2024 Jul; 16(28):36911-36922. PubMed ID: 38965667
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Exploration of Alloying Elements of High Specific Modulus Al-Li Alloy Based on Machine Learning.
    Li H; Li X; Li Y; Gao G; Wen K; Li Z; Zhang Y; Xiong B
    Materials (Basel); 2023 Dec; 17(1):. PubMed ID: 38203946
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine-Learning Predictions of Critical Temperatures from Chemical Compositions of Superconductors.
    Jung SG; Jung G; Cole JM
    J Chem Inf Model; 2024 Oct; 64(19):7349-7375. PubMed ID: 39287336
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Machine learning assisted prediction of the Young's modulus of compositionally complex alloys.
    Khakurel H; Taufique MFN; Roy A; Balasubramanian G; Ouyang G; Cui J; Johnson DD; Devanathan R
    Sci Rep; 2021 Aug; 11(1):17149. PubMed ID: 34433841
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Enhanced osteoporotic fracture prediction in postmenopausal women using Bayesian optimization of machine learning models with genetic risk score.
    Wu Q; Dai J
    J Bone Miner Res; 2024 May; 39(4):462-472. PubMed ID: 38477741
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Composition Design Strategy for High Entropy Amorphous Alloys.
    Ding H; Zhang Q; Yao K
    Materials (Basel); 2024 Jan; 17(2):. PubMed ID: 38255621
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Data-driven analysis and prediction of stable phases for high-entropy alloy design.
    Peivaste I; Jossou E; Tiamiyu AA
    Sci Rep; 2023 Dec; 13(1):22556. PubMed ID: 38110634
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Accelerated Design for High-Entropy Alloys Based on Machine Learning and Multiobjective Optimization.
    Ma Y; Li M; Mu Y; Wang G; Lu W
    J Chem Inf Model; 2023 Oct; 63(19):6029-6042. PubMed ID: 37749914
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning-enabled high-entropy alloy discovery.
    Rao Z; Tung PY; Xie R; Wei Y; Zhang H; Ferrari A; Klaver TPC; Körmann F; Sukumar PT; Kwiatkowski da Silva A; Chen Y; Li Z; Ponge D; Neugebauer J; Gutfleisch O; Bauer S; Raabe D
    Science; 2022 Oct; 378(6615):78-85. PubMed ID: 36201584
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping.
    Razavi-Termeh SV; Sadeghi-Niaraki A; Farhangi F; Khiadani M; Pirasteh S; Choi SM
    Chemosphere; 2024 Sep; 363():142859. PubMed ID: 39025307
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Experimentally validated inverse design of multi-property Fe-Co-Ni alloys.
    Padhy SP; Chaudhary V; Lim YF; Zhu R; Thway M; Hippalgaonkar K; Ramanujan RV
    iScience; 2024 May; 27(5):109723. PubMed ID: 38706846
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Design of high bulk moduli high entropy alloys using machine learning.
    Kandavalli M; Agarwal A; Poonia A; Kishor M; Ayyagari KPR
    Sci Rep; 2023 Nov; 13(1):20504. PubMed ID: 37993607
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Machine Learning Assisted Exploration of High Entropy Alloy-Based Catalysts for Selective CO
    Roy D; Mandal SC; Pathak B
    J Phys Chem Lett; 2022 Jun; 13(25):5991-6002. PubMed ID: 35737450
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.