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 *

111 related articles for article (PubMed ID: 38735182)

  • 1. Machine learning for predicting halogen radical reactivity toward aqueous organic chemicals.
    Liang Y; Huangfu X; Huang R; Han Z; Wu S; Wang J; Long X; Ma J; He Q
    J Hazard Mater; 2024 Jul; 472():134501. PubMed ID: 38735182
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Machine learning approaches to predict the apparent rate constants for aqueous organic compounds by ferrate.
    Zheng SS; Guo WQ; Lu H; Si QS; Liu BH; Wang HZ; Zhao Q; Jia WR; Yu TP
    J Environ Manage; 2023 Mar; 329():116904. PubMed ID: 36528943
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Application of machine learning and deep learning methods for hydrated electron rate constant prediction.
    Zheng S; Guo W; Li C; Sun Y; Zhao Q; Lu H; Si Q; Wang H
    Environ Res; 2023 Aug; 231(Pt 1):115996. PubMed ID: 37105290
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A new perspective on predicting the reaction rate constants of hydrated electrons for organic contaminants: Exploring molecular structure characterization methods and ambient conditions.
    Zhu T; Li S; Li L; Tao C
    Sci Total Environ; 2023 Dec; 904():166316. PubMed ID: 37591396
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Prediction of free radical reactions toward organic pollutants with easily accessible molecular descriptors.
    Zhang G; Zhu Q; Zheng H; Zhang S; Ma J
    Chemosphere; 2024 Jan; 346():140660. PubMed ID: 37951397
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Predicting adsorption of organic compounds onto graphene and black phosphorus by molecular dynamics and machine learning.
    Su L; Wang Z; Wang Y; Xiao Z; Xia D; Zhang S; Chen J
    Environ Sci Pollut Res Int; 2023 Oct; 30(50):108846-108854. PubMed ID: 37759049
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models.
    Tayyebi A; Alshami AS; Rabiei Z; Yu X; Ismail N; Talukder MJ; Power J
    J Cheminform; 2023 Oct; 15(1):99. PubMed ID: 37853492
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting reactivity dynamics of halogen species and trace organic contaminants using machine learning models.
    Zhu J; Huang Y; Yi Q; Bu L; Zhou S; Shi Z
    Chemosphere; 2024 Jan; 346():140659. PubMed ID: 37949193
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Improved GNNs for Log 
    Duan YJ; Fu L; Zhang XC; Long TZ; He YH; Liu ZQ; Lu AP; Deng YF; Hsieh CY; Hou TJ; Cao DS
    J Chem Inf Model; 2023 Apr; 63(8):2345-2359. PubMed ID: 37000044
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Quantitative structure-property relationships for the calculation of the soil adsorption coefficient using machine learning algorithms with calculated chemical properties from open-source software.
    Kobayashi Y; Yoshida K
    Environ Res; 2021 May; 196():110363. PubMed ID: 33148423
    [TBL] [Abstract][Full Text] [Related]  

  • 11. "
    Sanches-Neto FO; Dias-Silva JR; Keng Queiroz Junior LH; Carvalho-Silva VH
    Environ Sci Technol; 2021 Sep; 55(18):12437-12448. PubMed ID: 34473479
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Improving predictions and understanding of primary and ultimate biodegradation rates with machine learning models.
    Jiang S; Liang Y; Shi S; Wu C; Shi Z
    Sci Total Environ; 2023 Dec; 904():166623. PubMed ID: 37652371
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine Learning Models for Predicting Influential Factors of Early Outcomes in Acute Ischemic Stroke: Registry-Based Study.
    Su PY; Wei YC; Luo H; Liu CH; Huang WY; Chen KF; Lin CP; Wei HY; Lee TH
    JMIR Med Inform; 2022 Mar; 10(3):e32508. PubMed ID: 35072631
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Optimal Dimensioning of Retaining Walls Using Explainable Ensemble Learning Algorithms.
    Bekdaş G; Cakiroglu C; Kim S; Geem ZW
    Materials (Basel); 2022 Jul; 15(14):. PubMed ID: 35888460
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
    Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine-learning based prediction models for assessing skin irritation and corrosion potential of liquid chemicals using physicochemical properties by XGBoost.
    Kang Y; Kim MG; Lim KM
    Toxicol Res; 2023 Apr; 39(2):295-305. PubMed ID: 37008690
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Count-Based Morgan Fingerprint: A More Efficient and Interpretable Molecular Representation in Developing Machine Learning-Based Predictive Regression Models for Water Contaminants' Activities and Properties.
    Zhong S; Guan X
    Environ Sci Technol; 2023 Nov; 57(46):18193-18202. PubMed ID: 37406199
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MLASM: Machine learning based prediction of anticancer small molecules.
    Balaji PD; Selvam S; Sohn H; Madhavan T
    Mol Divers; 2024 Aug; 28(4):2153-2161. PubMed ID: 38554168
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Ensemble machine learning model trained on a new synthesized dataset generalizes well for stress prediction using wearable devices.
    Vos G; Trinh K; Sarnyai Z; Rahimi Azghadi M
    J Biomed Inform; 2023 Dec; 148():104556. PubMed ID: 38048895
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Application of machine learning approaches to predict the 5-year survival status of patients with esophageal cancer.
    Gong X; Zheng B; Xu G; Chen H; Chen C
    J Thorac Dis; 2021 Nov; 13(11):6240-6251. PubMed ID: 34992804
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.