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 *

117 related articles for article (PubMed ID: 37983482)

  • 1. Identification of High-Reliability Regions of Machine Learning Predictions Based on Materials Chemistry.
    Askenazi EM; Lazar EA; Grinberg I
    J Chem Inf Model; 2023 Dec; 63(23):7350-7362. PubMed ID: 37983482
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Hybrid Modelling by Machine Learning Corrections of Analytical Model Predictions towards High-Fidelity Simulation Solutions.
    Bock FE; Keller S; Huber N; Klusemann B
    Materials (Basel); 2021 Apr; 14(8):. PubMed ID: 33920078
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Materials Prediction via Classification Learning.
    Balachandran PV; Theiler J; Rondinelli JM; Lookman T
    Sci Rep; 2015 Aug; 5():13285. PubMed ID: 26304800
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Characterizing Uncertainty in Machine Learning for Chemistry.
    Heid E; McGill CJ; Vermeire FH; Green WH
    J Chem Inf Model; 2023 Jul; 63(13):4012-4029. PubMed ID: 37338239
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluating pointwise reliability of machine learning prediction.
    Nicora G; Rios M; Abu-Hanna A; Bellazzi R
    J Biomed Inform; 2022 Mar; 127():103996. PubMed ID: 35041981
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Planning Implications Related to Sterilization-Sensitive Science Investigations Associated with Mars Sample Return (MSR).
    Velbel MA; Cockell CS; Glavin DP; Marty B; Regberg AB; Smith AL; Tosca NJ; Wadhwa M; Kminek G; Meyer MA; Beaty DW; Carrier BL; Haltigin T; Hays LE; Agee CB; Busemann H; Cavalazzi B; Debaille V; Grady MM; Hauber E; Hutzler A; McCubbin FM; Pratt LM; Smith CL; Summons RE; Swindle TD; Tait KT; Udry A; Usui T; Westall F; Zorzano MP
    Astrobiology; 2022 Jun; 22(S1):S112-S164. PubMed ID: 34904892
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine-learning Models Predict 30-Day Mortality, Cardiovascular Complications, and Respiratory Complications After Aseptic Revision Total Joint Arthroplasty.
    Abraham VM; Booth G; Geiger P; Balazs GC; Goldman A
    Clin Orthop Relat Res; 2022 Nov; 480(11):2137-2145. PubMed ID: 35767804
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Effect of Flattened Structures of Molecules and Materials on Machine Learning Model Training.
    de Azevedo LC; Prati RC
    J Chem Inf Model; 2023 Sep; 63(17):5446-5456. PubMed ID: 37625081
    [TBL] [Abstract][Full Text] [Related]  

  • 10. ADMET Evaluation in Drug Discovery. Part 17: Development of Quantitative and Qualitative Prediction Models for Chemical-Induced Respiratory Toxicity.
    Lei T; Chen F; Liu H; Sun H; Kang Y; Li D; Li Y; Hou T
    Mol Pharm; 2017 Jul; 14(7):2407-2421. PubMed ID: 28595388
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Feature-Assisted Machine Learning for Predicting Band Gaps of Binary Semiconductors.
    Huo S; Zhang S; Wu Q; Zhang X
    Nanomaterials (Basel); 2024 Feb; 14(5):. PubMed ID: 38470776
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Genetic Optimization of Training Sets for Improved Machine Learning Models of Molecular Properties.
    Browning NJ; Ramakrishnan R; von Lilienfeld OA; Roethlisberger U
    J Phys Chem Lett; 2017 Apr; 8(7):1351-1359. PubMed ID: 28257210
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams.
    Rossignol H; Minotakis M; Cobelli M; Sanvito S
    J Chem Inf Model; 2024 Mar; 64(6):1828-1840. PubMed ID: 38271693
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design.
    Janet JP; Duan C; Nandy A; Liu F; Kulik HJ
    Acc Chem Res; 2021 Feb; 54(3):532-545. PubMed ID: 33480674
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models.
    Conn JGM; Carter JW; Conn JJA; Subramanian V; Baxter A; Engkvist O; Llinas A; Ratkova EL; Pickett SD; McDonagh JL; Palmer DS
    J Chem Inf Model; 2023 Feb; 63(4):1099-1113. PubMed ID: 36758178
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia.
    Batra R; Pilania G; Uberuaga BP; Ramprasad R
    ACS Appl Mater Interfaces; 2019 Jul; 11(28):24906-24918. PubMed ID: 30990303
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Demystifying machine learning: a primer for physicians.
    Scott IA
    Intern Med J; 2021 Sep; 51(9):1388-1400. PubMed ID: 33462882
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine Learning Prediction on Properties of Nanoporous Materials Utilizing Pore Geometry Barcodes.
    Zhang X; Cui J; Zhang K; Wu J; Lee Y
    J Chem Inf Model; 2019 Nov; 59(11):4636-4644. PubMed ID: 31661958
    [TBL] [Abstract][Full Text] [Related]  

  • 19. NJmat: Data-Driven Machine Learning Interface to Accelerate Material Design.
    Huang Y; Zhang L; Deng H; Mao J
    J Chem Inf Model; 2024 Aug; 64(16):6477-6491. PubMed ID: 39133673
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Cross-validation and out-of-sample testing of physical activity intensity predictions with a wrist-worn accelerometer.
    Montoye AHK; Westgate BS; Fonley MR; Pfeiffer KA
    J Appl Physiol (1985); 2018 May; 124(5):1284-1293. PubMed ID: 29369742
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.