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 *

144 related articles for article (PubMed ID: 32626610)

  • 21. From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2.
    Weaver WN; Smith SA
    Appl Plant Sci; 2023; 11(5):e11548. PubMed ID: 37915430
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Instance segmentation for the fine detection of crop and weed plants by precision agricultural robots.
    Champ J; Mora-Fallas A; Goëau H; Mata-Montero E; Bonnet P; Joly A
    Appl Plant Sci; 2020 Jul; 8(7):e11373. PubMed ID: 32765972
    [TBL] [Abstract][Full Text] [Related]  

  • 23. An algorithm competition for automatic species identification from herbarium specimens.
    Little DP; Tulig M; Tan KC; Liu Y; Belongie S; Kaeser-Chen C; Michelangeli FA; Panesar K; Guha RV; Ambrose BA
    Appl Plant Sci; 2020 Jun; 8(6):e11365. PubMed ID: 32626608
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Going deeper in the automated identification of Herbarium specimens.
    Carranza-Rojas J; Goeau H; Bonnet P; Mata-Montero E; Joly A
    BMC Evol Biol; 2017 Aug; 17(1):181. PubMed ID: 28797242
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Digitization protocol for scoring reproductive phenology from herbarium specimens of seed plants.
    Yost JM; Sweeney PW; Gilbert E; Nelson G; Guralnick R; Gallinat AS; Ellwood ER; Rossington N; Willis CG; Blum SD; Walls RL; Haston EM; Denslow MW; Zohner CM; Morris AB; Stucky BJ; Carter JR; Baxter DG; Bolmgren K; Denny EG; Dean E; Pearson KD; Davis CC; Mishler BD; Soltis PS; Mazer SJ
    Appl Plant Sci; 2018 Feb; 6(2):e1022. PubMed ID: 29732253
    [TBL] [Abstract][Full Text] [Related]  

  • 26. LeafMachine: Using machine learning to automate leaf trait extraction from digitized herbarium specimens.
    Weaver WN; Ng J; Laport RG
    Appl Plant Sci; 2020 Jun; 8(6):e11367. PubMed ID: 32626609
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Using Convolutional Neural Networks to Efficiently Extract Immense Phenological Data From Community Science Images.
    Reeb RA; Aziz N; Lapp SM; Kitzes J; Heberling JM; Kuebbing SE
    Front Plant Sci; 2021; 12():787407. PubMed ID: 35111176
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Can Artificial Intelligence Help in the Study of Vegetative Growth Patterns from Herbarium Collections? An Evaluation of the Tropical Flora of the French Guiana Forest.
    Goëau H; Lorieul T; Heuret P; Joly A; Bonnet P
    Plants (Basel); 2022 Feb; 11(4):. PubMed ID: 35214863
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States.
    Park DS; Breckheimer I; Williams AC; Law E; Ellison AM; Davis CC
    Philos Trans R Soc Lond B Biol Sci; 2018 Nov; 374(1763):. PubMed ID: 30455212
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Phenological responses to climate change based on a hundred years of herbarium collections of tropical Melastomataceae.
    Lima DF; Mello JHF; Lopes IT; Forzza RC; Goldenberg R; Freitas L
    PLoS One; 2021; 16(5):e0251360. PubMed ID: 33961684
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Overlooked climate parameters best predict flowering onset: Assessing phenological models using the elastic net.
    Park IW; Mazer SJ
    Glob Chang Biol; 2018 Dec; 24(12):5972-5984. PubMed ID: 30218548
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A convolutional neural network for segmentation of yeast cells without manual training annotations.
    Kruitbosch HT; Mzayek Y; Omlor S; Guerra P; Milias-Argeitis A
    Bioinformatics; 2022 Feb; 38(5):1427-1433. PubMed ID: 34893817
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Combining weakly and strongly supervised learning improves strong supervision in Gleason pattern classification.
    Otálora S; Marini N; Müller H; Atzori M
    BMC Med Imaging; 2021 May; 21(1):77. PubMed ID: 33964886
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.
    Lee JH; Han SS; Kim YH; Lee C; Kim I
    Oral Surg Oral Med Oral Pathol Oral Radiol; 2020 Jun; 129(6):635-642. PubMed ID: 31992524
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Erratum: Eyestalk Ablation to Increase Ovarian Maturation in Mud Crabs.
    J Vis Exp; 2023 May; (195):. PubMed ID: 37235796
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images.
    Zhuang M; Chen Z; Wang H; Tang H; He J; Qin B; Yang Y; Jin X; Yu M; Jin B; Li T; Kettunen L
    Int J Comput Assist Radiol Surg; 2023 Feb; 18(2):379-394. PubMed ID: 36048319
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.
    Jones CA; Daehler CC
    PeerJ; 2018; 6():e4576. PubMed ID: 29632745
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Automating Ground Truth Annotations for Gland Segmentation Through Immunohistochemistry.
    Kataria T; Rajamani S; Ayubi AB; Bronner M; Jedrzkiewicz J; Knudsen BS; Elhabian SY
    Mod Pathol; 2023 Dec; 36(12):100331. PubMed ID: 37716506
    [TBL] [Abstract][Full Text] [Related]  

  • 39. New directions in tropical phenology.
    Davis CC; Lyra GM; Park DS; Asprino R; Maruyama R; Torquato D; Cook BI; Ellison AM
    Trends Ecol Evol; 2022 Aug; 37(8):683-693. PubMed ID: 35680467
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Macroevolutionary history predicts flowering time but not phenological sensitivity to temperature in grasses.
    Neto-Bradley BM; Whitton J; Lipsen LPJ; Pennell MW
    Am J Bot; 2021 May; 108(5):893-902. PubMed ID: 33948930
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.