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 *

174 related articles for article (PubMed ID: 34415142)

  • 21. Perspective: Big Data and Machine Learning Could Help Advance Nutritional Epidemiology.
    Morgenstern JD; Rosella LC; Costa AP; de Souza RJ; Anderson LN
    Adv Nutr; 2021 Jun; 12(3):621-631. PubMed ID: 33606879
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Systems Biology and Machine Learning in Plant-Pathogen Interactions.
    Mishra B; Kumar N; Mukhtar MS
    Mol Plant Microbe Interact; 2019 Jan; 32(1):45-55. PubMed ID: 30418085
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods.
    Luo G; Stone BL; Johnson MD; Tarczy-Hornoch P; Wilcox AB; Mooney SD; Sheng X; Haug PJ; Nkoy FL
    JMIR Res Protoc; 2017 Aug; 6(8):e175. PubMed ID: 28851678
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Classifying smoking urges via machine learning.
    Dumortier A; Beckjord E; Shiffman S; Sejdić E
    Comput Methods Programs Biomed; 2016 Dec; 137():203-213. PubMed ID: 28110725
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Nurses "Seeing Forest for the Trees" in the Age of Machine Learning: Using Nursing Knowledge to Improve Relevance and Performance.
    Kwon JY; Karim ME; Topaz M; Currie LM
    Comput Inform Nurs; 2019 Apr; 37(4):203-212. PubMed ID: 30688670
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Machine Learning-Assisted Design of Material Properties.
    Kadulkar S; Sherman ZM; Ganesan V; Truskett TM
    Annu Rev Chem Biomol Eng; 2022 Jun; 13():235-254. PubMed ID: 35300515
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells.
    Santi D; Spaggiari G; Casonati A; Casarini L; Grassi R; Vecchi B; Roli L; De Santis MC; Orlando G; Gravotta E; Baraldi E; Setti M; Trenti T; Simoni M
    Andrology; 2020 Sep; 8(5):1021-1029. PubMed ID: 32449608
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Usages of Spark Framework with Different Machine Learning Algorithms.
    Ali Mohamed M; El-Henawy IM; Salah A
    Comput Intell Neurosci; 2021; 2021():1896953. PubMed ID: 34367270
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
    Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G
    Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases.
    Alqaissi EY; Alotaibi FS; Ramzan MS
    Comput Math Methods Med; 2022; 2022():6902321. PubMed ID: 35693267
    [TBL] [Abstract][Full Text] [Related]  

  • 31. A comparative study on machine learning based algorithms for prediction of motorcycle crash severity.
    Wahab L; Jiang H
    PLoS One; 2019; 14(4):e0214966. PubMed ID: 30947250
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Predicting of anaphylaxis in big data EMR by exploring machine learning approaches.
    Segura-Bedmar I; Colón-Ruíz C; Tejedor-Alonso MÁ; Moro-Moro M
    J Biomed Inform; 2018 Nov; 87():50-59. PubMed ID: 30266231
    [TBL] [Abstract][Full Text] [Related]  

  • 33. New Machine Learning Applications to Accelerate Personalized Medicine in Breast Cancer: Rise of the Support Vector Machines.
    Ozer ME; Sarica PO; Arga KY
    OMICS; 2020 May; 24(5):241-246. PubMed ID: 32228365
    [TBL] [Abstract][Full Text] [Related]  

  • 34. The state of art on the prediction of efficiency and modeling of the processes of pollutants removal based on machine learning.
    Taoufik N; Boumya W; Achak M; Chennouk H; Dewil R; Barka N
    Sci Total Environ; 2022 Feb; 807(Pt 1):150554. PubMed ID: 34597573
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.
    Ryo M; Jeschke JM; Rillig MC; Heger T
    Res Synth Methods; 2020 Jan; 11(1):66-73. PubMed ID: 31219681
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Big data and machine learning for materials science.
    Rodrigues JF; Florea L; de Oliveira MCF; Diamond D; Oliveira ON
    Discov Mater; 2021; 1(1):12. PubMed ID: 33899049
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.
    Kaiser TM; Burger PB
    Molecules; 2019 Jun; 24(11):. PubMed ID: 31167452
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Intelligent Machine Learning Approach for Effective Recognition of Diabetes in E-Healthcare Using Clinical Data.
    Haq AU; Li JP; Khan J; Memon MH; Nazir S; Ahmad S; Khan GA; Ali A
    Sensors (Basel); 2020 May; 20(9):. PubMed ID: 32384737
    [TBL] [Abstract][Full Text] [Related]  

  • 39. A machine learning approach for handling big data produced by high resolution mass spectrometry after data independent acquisition of small molecules - Proof of concept study using an artificial neural network for sample classification.
    Streun GL; Elmiger MP; Dobay A; Ebert L; Kraemer T
    Drug Test Anal; 2020 Jun; 12(6):836-845. PubMed ID: 31997574
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.
    Cole-Lewis H; Varghese A; Sanders A; Schwarz M; Pugatch J; Augustson E
    J Med Internet Res; 2015 Aug; 17(8):e208. PubMed ID: 26307512
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.