BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

119 related articles for article (PubMed ID: 37683105)

  • 1. Interpretable XGBoost-SHAP Model Predicts Nanoparticles Delivery Efficiency Based on Tumor Genomic Mutations and Nanoparticle Properties.
    Ma X; Tang Y; Wang C; Li Y; Zhang J; Luo Y; Xu Z; Wu F; Wang S
    ACS Appl Bio Mater; 2023 Oct; 6(10):4326-4335. PubMed ID: 37683105
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches.
    Lin Z; Chou WC; Cheng YH; He C; Monteiro-Riviere NA; Riviere JE
    Int J Nanomedicine; 2022; 17():1365-1379. PubMed ID: 35360005
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An artificial intelligence-assisted physiologically-based pharmacokinetic model to predict nanoparticle delivery to tumors in mice.
    Chou WC; Chen Q; Yuan L; Cheng YH; He C; Monteiro-Riviere NA; Riviere JE; Lin Z
    J Control Release; 2023 Sep; 361():53-63. PubMed ID: 37499908
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.
    Huang J; Chen H; Deng J; Liu X; Shu T; Yin C; Duan M; Fu L; Wang K; Zeng S
    Front Neurol; 2023; 14():1185447. PubMed ID: 37614971
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.
    Li J; Liu S; Hu Y; Zhu L; Mao Y; Liu J
    J Med Internet Res; 2022 Aug; 24(8):e38082. PubMed ID: 35943767
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Interpretation of ensemble learning to predict water quality using explainable artificial intelligence.
    Park J; Lee WH; Kim KT; Park CY; Lee S; Heo TY
    Sci Total Environ; 2022 Aug; 832():155070. PubMed ID: 35398119
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Meta-Analysis of Nanoparticle Distribution in Tumors and Major Organs in Tumor-Bearing Mice.
    Chen Q; Yuan L; Chou WC; Cheng YH; He C; Monteiro-Riviere NA; Riviere JE; Lin Z
    ACS Nano; 2023 Oct; 17(20):19810-19831. PubMed ID: 37812732
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tumor-Acidity-Cleavable Maleic Acid Amide (TACMAA): A Powerful Tool for Designing Smart Nanoparticles To Overcome Delivery Barriers in Cancer Nanomedicine.
    Du JZ; Li HJ; Wang J
    Acc Chem Res; 2018 Nov; 51(11):2848-2856. PubMed ID: 30346728
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A high-throughput bioimaging study to assess the impact of chitosan-based nanoparticle degradation on DNA delivery performance.
    Gomes CP; Varela-Moreira A; Leiro V; Lopes CDF; Moreno PMD; Gomez-Lazaro M; Pêgo AP
    Acta Biomater; 2016 Dec; 46():129-140. PubMed ID: 27686038
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [Application of machine learning model based on XGBoost algorithm in early prediction of patients with acute severe pancreatitis].
    Gao X; Lin J; Wu A; Gu H; Liu X; Yin M; Zhou Z; Zhang R; Xu C; Zhu J
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Apr; 35(4):421-426. PubMed ID: 37308200
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pharmacokinetics and tumor delivery of nanoparticles.
    Yuan L; Chen Q; Riviere JE; Lin Z
    J Drug Deliv Sci Technol; 2023 May; 83():. PubMed ID: 38037664
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Development of a Physiologically-Based Mathematical Model for Quantifying Nanoparticle Distribution in Tumors.
    Dogra P; Chuang YL; Butner JD; Cristini V; Wang Z
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():2852-2855. PubMed ID: 31946487
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP.
    Alabi RO; Elmusrati M; Leivo I; Almangush A; Mäkitie AA
    Sci Rep; 2023 Jun; 13(1):8984. PubMed ID: 37268685
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Explainable artificial intelligence model for identifying COVID-19 gene biomarkers.
    Yagin FH; Cicek İB; Alkhateeb A; Yagin B; Colak C; Azzeh M; Akbulut S
    Comput Biol Med; 2023 Mar; 154():106619. PubMed ID: 36738712
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of transport behavior of nanoparticles using machine learning algorithm: Physical significance of important features.
    Banerjee S; Bhavna K; Raychoudhury T
    J Contam Hydrol; 2023 Sep; 258():104237. PubMed ID: 37666037
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery.
    Dogra P; Butner JD; Ruiz Ramírez J; Chuang YL; Noureddine A; Jeffrey Brinker C; Cristini V; Wang Z
    Comput Struct Biotechnol J; 2020; 18():518-531. PubMed ID: 32206211
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning.
    Lai Y; Lin X; Lin C; Lin X; Chen Z; Zhang L
    Front Pharmacol; 2022; 13():975774. PubMed ID: 36059957
    [No Abstract]   [Full Text] [Related]  

  • 18. Interpretable machine-learning model for real-time, clustered risk factor analysis of sepsis and septic death in critical care.
    Jiang Z; Bo L; Wang L; Xie Y; Cao J; Yao Y; Lu W; Deng X; Yang T; Bian J
    Comput Methods Programs Biomed; 2023 Nov; 241():107772. PubMed ID: 37657148
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Nano-Bio Interactions in Cancer: From Therapeutics Delivery to Early Detection.
    Liu Y; Wang J; Xiong Q; Hornburg D; Tao W; Farokhzad OC
    Acc Chem Res; 2021 Jan; 54(2):291-301. PubMed ID: 33180454
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Interpretable prediction of mortality in liver transplant recipients based on machine learning.
    Zhang X; Gavaldà R; Baixeries J
    Comput Biol Med; 2022 Dec; 151(Pt A):106188. PubMed ID: 36306583
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.