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 *

1128 related articles for article (PubMed ID: 34202291)

  • 1. Review: Application of Artificial Intelligence in Phenomics.
    Nabwire S; Suh HK; Kim MS; Baek I; Cho BK
    Sensors (Basel); 2021 Jun; 21(13):. PubMed ID: 34202291
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks.
    Ubbens JR; Stavness I
    Front Plant Sci; 2017; 8():1190. PubMed ID: 28736569
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Ready, Steady, Go AI: A practical tutorial on fundamentals of artificial intelligence and its applications in phenomics image analysis.
    Nakhle F; Harfouche AL
    Patterns (N Y); 2021 Sep; 2(9):100323. PubMed ID: 34553170
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Applications of Artificial Intelligence in Climate-Resilient Smart-Crop Breeding.
    Khan MHU; Wang S; Wang J; Ahmar S; Saeed S; Khan SU; Xu X; Chen H; Bhat JA; Feng X
    Int J Mol Sci; 2022 Sep; 23(19):. PubMed ID: 36232455
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep Learning in Image-Based Plant Phenotyping.
    Murphy KM; Ludwig E; Gutierrez J; Gehan MA
    Annu Rev Plant Biol; 2024 Jul; 75(1):771-795. PubMed ID: 38382904
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A primer on artificial intelligence in plant digital phenomics: embarking on the data to insights journey.
    Harfouche AL; Nakhle F; Harfouche AH; Sardella OG; Dart E; Jacobson D
    Trends Plant Sci; 2023 Feb; 28(2):154-184. PubMed ID: 36167648
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops.
    Furbank RT; Jimenez-Berni JA; George-Jaeggli B; Potgieter AB; Deery DM
    New Phytol; 2019 Sep; 223(4):1714-1727. PubMed ID: 30937909
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence.
    Harfouche AL; Jacobson DA; Kainer D; Romero JC; Harfouche AH; Scarascia Mugnozza G; Moshelion M; Tuskan GA; Keurentjes JJB; Altman A
    Trends Biotechnol; 2019 Nov; 37(11):1217-1235. PubMed ID: 31235329
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application.
    Bellemo V; Lim G; Rim TH; Tan GSW; Cheung CY; Sadda S; He MG; Tufail A; Lee ML; Hsu W; Ting DSW
    Curr Diab Rep; 2019 Jul; 19(9):72. PubMed ID: 31367962
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Machine Learning for Image Analysis: Leaf Disease Segmentation.
    F Danilevicz M; Bayer PE
    Methods Mol Biol; 2022; 2443():429-449. PubMed ID: 35037219
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives.
    Singh AK; Ganapathysubramanian B; Sarkar S; Singh A
    Trends Plant Sci; 2018 Oct; 23(10):883-898. PubMed ID: 30104148
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning and Artificial Intelligence: A Paradigm Shift in Big Data-Driven Drug Design and Discovery.
    Pasrija P; Jha P; Upadhyaya P; Khan MS; Chopra M
    Curr Top Med Chem; 2022; 22(20):1692-1727. PubMed ID: 35786336
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Temporal Phenomics - A Powerful Approach Using AI to Achieve "Earlier Medicine".
    Li YJ
    Stud Health Technol Inform; 2022 Oct; 300():177-179. PubMed ID: 36300410
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computational aspects underlying genome to phenome analysis in plants.
    Bolger AM; Poorter H; Dumschott K; Bolger ME; Arend D; Osorio S; Gundlach H; Mayer KFX; Lange M; Scholz U; Usadel B
    Plant J; 2019 Jan; 97(1):182-198. PubMed ID: 30500991
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Artificial intelligence as an emerging technology in the current care of neurological disorders.
    Patel UK; Anwar A; Saleem S; Malik P; Rasul B; Patel K; Yao R; Seshadri A; Yousufuddin M; Arumaithurai K
    J Neurol; 2021 May; 268(5):1623-1642. PubMed ID: 31451912
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture.
    Cembrowska-Lech D; Krzemińska A; Miller T; Nowakowska A; Adamski C; Radaczyńska M; Mikiciuk G; Mikiciuk M
    Biology (Basel); 2023 Sep; 12(10):. PubMed ID: 37887008
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Crop Phenomics: Current Status and Perspectives.
    Zhao C; Zhang Y; Du J; Guo X; Wen W; Gu S; Wang J; Fan J
    Front Plant Sci; 2019; 10():714. PubMed ID: 31214228
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants.
    Gou C; Zafar S; Hasnain Z; Aslam N; Iqbal N; Abbas S; Li H; Li J; Chen B; Ragauskas AJ; Abbas M
    Front Biosci (Landmark Ed); 2024 Jan; 29(1):20. PubMed ID: 38287813
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives.
    Yang W; Feng H; Zhang X; Zhang J; Doonan JH; Batchelor WD; Xiong L; Yan J
    Mol Plant; 2020 Feb; 13(2):187-214. PubMed ID: 31981735
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Cell to whole-plant phenotyping: the best is yet to come.
    Dhondt S; Wuyts N; Inzé D
    Trends Plant Sci; 2013 Aug; 18(8):428-39. PubMed ID: 23706697
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 57.