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 *

142 related articles for article (PubMed ID: 35412988)

  • 21. Comparison of Artificial and Spiking Neural Networks on Digital Hardware.
    Davidson S; Furber SB
    Front Neurosci; 2021; 15():651141. PubMed ID: 33889071
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Constructing an E-Nose Using Metal-Ion-Induced Assembly of Graphene Oxide for Diagnosis of Lung Cancer via Exhaled Breath.
    Chen Q; Chen Z; Liu D; He Z; Wu J
    ACS Appl Mater Interfaces; 2020 Apr; 12(15):17713-17724. PubMed ID: 32203649
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Physicochemical parameters combined flash GC e-nose and artificial neural network for quality and volatile characterization of vinegar with different brewing techniques.
    Li Y; Fei C; Mao C; Ji D; Gong J; Qin Y; Qu L; Zhang W; Bian Z; Su L; Lu T
    Food Chem; 2022 Apr; 374():131658. PubMed ID: 34896949
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Electronic nose based on independent component analysis combined with partial least squares and artificial neural networks for wine prediction.
    Aguilera T; Lozano J; Paredes JA; Alvarez FJ; Suárez JI
    Sensors (Basel); 2012; 12(6):8055-72. PubMed ID: 22969387
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Hazardous Odor Recognition by CMAC Based Neural Networks.
    Bucak IÖ; Karlık B
    Sensors (Basel); 2009; 9(9):7308-19. PubMed ID: 22399997
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform.
    Patiño-Saucedo A; Rostro-Gonzalez H; Serrano-Gotarredona T; Linares-Barranco B
    Neural Netw; 2020 Jan; 121():319-328. PubMed ID: 31590013
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).
    Tan J; Kerr WL
    J Sci Food Agric; 2018 Aug; 98(10):3851-3859. PubMed ID: 29363771
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Evaluation of coffee roasting degree by using electronic nose and artificial neural network for off-line quality control.
    Romani S; Cevoli C; Fabbri A; Alessandrini L; Dalla Rosa M
    J Food Sci; 2012 Sep; 77(9):C960-5. PubMed ID: 22908932
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Rapid Identification Method for CH
    Yin J; Zhao Y; Peng Z; Ba F; Peng P; Liu X; Rong Q; Guo Y; Zhang Y
    Sensors (Basel); 2023 Mar; 23(6):. PubMed ID: 36991686
    [TBL] [Abstract][Full Text] [Related]  

  • 30. E-nose based rapid prediction of early mouldy grain using probabilistic neural networks.
    Ying X; Liu W; Hui G; Fu J
    Bioengineered; 2015; 6(4):222-6. PubMed ID: 25714125
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Classification for
    Guo Z; Guo C; Chen Q; Ouyang Q; Shi J; El-Seedi HR; Zou X
    Sensors (Basel); 2020 Apr; 20(7):. PubMed ID: 32283830
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Research on Distinguishing Fish Meal Quality Using Different Characteristic Parameters Based on Electronic Nose Technology.
    Li P; Ren Z; Shao K; Tan H; Niu Z
    Sensors (Basel); 2019 May; 19(9):. PubMed ID: 31075849
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Towards a chemiresistive sensor-integrated electronic nose: a review.
    Chiu SW; Tang KT
    Sensors (Basel); 2013 Oct; 13(10):14214-47. PubMed ID: 24152879
    [TBL] [Abstract][Full Text] [Related]  

  • 34. An E-nose and Convolution Neural Network based Recognition Method for Processed Products of Crataegi Fructus.
    Wang T; Chao Y; Yin F; Yang X; Hu C; Hu K
    Comb Chem High Throughput Screen; 2021; 24(7):921-932. PubMed ID: 32669076
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Chlorophenols identification in water using an electronic nose and ANNs (artificial neural networks) classification.
    Vázquez MJ; Lorenzo RA; Cela R
    Water Sci Technol; 2004; 49(9):99-105. PubMed ID: 15237613
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Design and Implementation of a Spiking Neural Network with Integrate-and-Fire Neuron Model for Pattern Recognition.
    Rashvand P; Ahmadzadeh MR; Shayegh F
    Int J Neural Syst; 2021 Mar; 31(3):2050073. PubMed ID: 33353527
    [TBL] [Abstract][Full Text] [Related]  

  • 37. An analog multilayer perceptron neural network for a portable electronic nose.
    Pan CH; Hsieh HY; Tang KT
    Sensors (Basel); 2012 Dec; 13(1):193-207. PubMed ID: 23262482
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Detection and classification of human body odor using an electronic nose.
    Wongchoosuk C; Lutz M; Kerdcharoen T
    Sensors (Basel); 2009; 9(9):7234-49. PubMed ID: 22399995
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Classification of odorants in the vapor phase using composite features for a portable e-nose system.
    Choi SI; Jeong GM; Kim C
    Sensors (Basel); 2012 Nov; 12(12):16182-93. PubMed ID: 23443373
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Qualitative identification of the edible oil storage period using a homemade portable electronic nose combined with multivariate analysis.
    Jiang H; He Y; Chen Q
    J Sci Food Agric; 2021 Jun; 101(8):3448-3456. PubMed ID: 33270243
    [TBL] [Abstract][Full Text] [Related]  

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