Performance evaluation of E-nose and E-tongue combined with machine learning for qualitative and quantitative assessment of bear bile powder

[1]  Lee M. Tatham,et al.  FXR inhibition may protect from SARS-CoV-2 infection by reducing ACE2 , 2022, Nature.

[2]  Meifeng Li,et al.  Rapid discrimination of the authenticity and geographical origin of bear bile powder using stable isotope ratio and elemental analysis , 2022, Analytical and Bioanalytical Chemistry.

[3]  Li Guo,et al.  Application of Stable Isotopes with Machine Learning Techniques for Identifying Aconiti Lateralis Radix Praeparata (Fuzi) Geographical Origins , 2022, Microchemical Journal.

[4]  L. Fu,et al.  Integrating spaceborne LiDAR and Sentinel-2 images to estimate forest aboveground biomass in Northern China , 2022, Carbon Balance and Management.

[5]  Li Yang,et al.  Rapid Identification of Bear Bile Powder from Other Bile Sources Using Chip-Based Nano-Electrospray Ionization Tandem Mass Spectrometry. , 2022, Rapid communications in mass spectrometry : RCM.

[6]  S. Uddin,et al.  Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction , 2022, Scientific Reports.

[7]  V. B. Kartha,et al.  Post-COVID syndrome screening through breath analysis using electronic nose technology , 2022, Analytical and Bioanalytical Chemistry.

[8]  Yitian Zhu,et al.  A novel strategy for discriminating different cultivation and screening odor and taste flavor compounds in Xinhui tangerine peel using E-nose, E-tongue, and chemometrics. , 2022, Food chemistry.

[9]  Xingyi Huang,et al.  Characterization of selected Chinese soybean paste based on flavor profiles using HS-SPME-GC/MS, E-nose and E-tongue combined with chemometrics. , 2021, Food chemistry.

[10]  Qiliang Li,et al.  Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods , 2021, Sensors.

[11]  Zheng-Tao Wang,et al.  Cultured bear bile powder ameliorates acute liver injury in cholestatic mice via inhibition of hepatic inflammation and apoptosis. , 2021, Journal of ethnopharmacology.

[12]  R. Liu,et al.  [Chemical constituents and pharmacological action of bile acids from animal:a review]. , 2021, Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica.

[13]  C. Pariante,et al.  From dried bear bile to molecular investigation: A systematic review of the effect of bile acids on cell apoptosis, oxidative stress and inflammation in the brain, across pre-clinical models of neurological, neurodegenerative and neuropsychiatric disorders , 2021, Brain, Behavior, and Immunity.

[14]  Claudia Gonzalez Viejo,et al.  Early Detection of Aphid Infestation and Insect-Plant Interaction Assessment in Wheat Using a Low-Cost Electronic Nose (E-Nose), Near-Infrared Spectroscopy and Machine Learning Modeling , 2021, Sensors.

[15]  Hongjun Yang,et al.  The qualitative and quantitative assessment of xiaochaihu granules based on e-eye, e-nose, e-tongue and chemometrics. , 2021, Journal of pharmaceutical and biomedical analysis.

[16]  Yongheng Yang,et al.  Application of E-nose technology combined with artificial neural network to predict total bacterial count in milk. , 2021, Journal of dairy science.

[17]  I. Blank,et al.  Application of gas chromatography-ion mobility spectrometry (GC-IMS) and ultrafast gas chromatography electronic-nose (uf-GC E-nose) to distinguish four Chinese freshwater fishes at both raw and cooked status. , 2021, Journal of food biochemistry.

[18]  Minghao Yuan,et al.  Research progress in the application of bile acid-drug conjugates: A “trojan horse” strategy , 2021, Steroids.

[19]  Saeed Mian Qaisar Signal-piloted processing and machine learning based efficient power quality disturbances recognition , 2021, PloS one.

[20]  Jun Deng,et al.  Prediction Model for Coal Spontaneous Combustion Based on SA-SVM , 2021, ACS omega.

[21]  Salimur Choudhury,et al.  Utilizing deep learning and graph mining to identify drug use on Twitter data , 2020, BMC Medical Informatics and Decision Making.

[22]  John-Lewis Zinia Zaukuu,et al.  Classification of Bee Pollen and Prediction of Sensory and Colorimetric Attributes—A Sensometric Fusion Approach by e-Nose, e-Tongue and NIR , 2020, Sensors.

[23]  Takeshi Murayama,et al.  Landmark annotation and mandibular lateral deviation analysis of posteroanterior cephalograms using a convolutional neural network , 2020, Journal of dental sciences.

[24]  Martin Harris,et al.  Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach , 2020, Sensors.

[25]  A. Wierzbicka,et al.  Rapid analysis of Baijiu volatile compounds fingerprint for their aroma and regional origin authenticity assessment. , 2020, Food chemistry.

[26]  Chunliu He,et al.  Automated classification of coronary plaque calcification in OCT pullbacks with 3D deep neural networks , 2020, Journal of biomedical optics.

[27]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[28]  Yuan Yuan,et al.  [DNA fingerprinting identification of bile power(bile)medicines]. , 2020, Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica.

[29]  S. Umbaugh,et al.  Medical infrared thermal imaging of canine appendicular bone neoplasia , 2019, BMC Veterinary Research.

[30]  Mohamad Sawan,et al.  Spatial resolution of local field potential signals in macaque V4 , 2019, Journal of neural engineering.

[31]  B. Pradhan,et al.  Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches , 2019, BMC Infectious Diseases.

[32]  Haiyan Yu,et al.  Characterization of key aroma compounds in Chinese rice wine using gas chromatography-mass spectrometry and gas chromatography-olfactometry. , 2019, Food chemistry.

[33]  Shuangcheng Ma,et al.  Analysis of the fingerprint profile of bioactive constituents of traditional Chinese medicinal materials derived from animal bile using the HPLC-ELSD and chemometric methods: An application of a reference scaleplate. , 2019, Journal of pharmaceutical and biomedical analysis.

[34]  María Lluch-Senar,et al.  Determination of the Gene Regulatory Network of a Genome-Reduced Bacterium Highlights Alternative Regulation Independent of Transcription Factors , 2019, Cell systems.

[35]  M. Chiogna,et al.  MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules , 2019, Nucleic acids research.

[36]  Zhenbo Wei,et al.  Combination of an E-Nose and an E-Tongue for Adulteration Detection of Minced Mutton Mixed with Pork , 2019, Journal of Food Quality.

[37]  Aling Shen,et al.  Bear Bile Powder Inhibits Growth of Hepatocellular Carcinoma via Suppressing STAT3 Signaling Pathway in Mice , 2019, Chinese Journal of Integrative Medicine.

[38]  Kyriakos C. Stylianou,et al.  Capturing chemical intuition in synthesis of metal-organic frameworks , 2019, Nature Communications.

[39]  Bin Han,et al.  Discrimination of Two Cultivars of Alpinia Officinarum Hance Using an Electronic Nose and Gas Chromatography-Mass Spectrometry Coupled with Chemometrics , 2019, Sensors.

[40]  Hongmei Zhang,et al.  Detection of bitterness and astringency of green tea with different taste by electronic nose and tongue , 2018, PloS one.

[41]  Yu Gu,et al.  Bionic Electronic Nose Based on MOS Sensors Array and Machine Learning Algorithms Used for Wine Properties Detection , 2018, Sensors.

[42]  Hongwei Wu,et al.  Determination of Bitterness of Andrographis Herba Based on Electronic Tongue Technology and Discovery of the Key Compounds of Bitter Substances , 2018, Molecules.

[43]  Linfang Huang,et al.  Discrimination and Geographical Origin Prediction of Cynomorium songaricum Rupr. from Different Growing Areas in China by an Electronic Tongue , 2018, Journal of analytical methods in chemistry.

[44]  Zheng-Tao Wang,et al.  [Systematical analysis of multiple components in drainage bear bile powder from different sources]. , 2018, Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica.

[45]  Xiang Zhang,et al.  HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring , 2018, IEEE Journal of Biomedical and Health Informatics.

[46]  Donghua Di,et al.  Preparation and toxicity evaluation of a novel nattokinase-tauroursodeoxycholate complex , 2017, Asian journal of pharmaceutical sciences.

[47]  Jun Wang,et al.  The prediction of food additives in the fruit juice based on electronic nose with chemometrics. , 2017, Food chemistry.

[48]  Chun-Wei Tung,et al.  Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens , 2017, Scientific Reports.

[49]  Joong-Ho Kwon,et al.  Application of E-tongue, E-nose, and MS-E-nose for discriminating aged vinegars based on taste and aroma profiles , 2016, Food Science and Biotechnology.

[50]  S. Görög Identification in drug quality control and drug research , 2015 .

[51]  A. Hofmann,et al.  Key discoveries in bile acid chemistry and biology and their clinical applications: history of the last eight decades , 2014, Journal of Lipid Research.

[52]  A. Zhang,et al.  Metabolomics and proteomics approaches to characterize and assess proteins of bear bile powder for hepatitis C virus. , 2013, Chinese journal of natural medicines.

[53]  X. Qiao,et al.  Differentiation of various traditional Chinese medicines derived from animal bile and gallstone: simultaneous determination of bile acids by liquid chromatography coupled with triple quadrupole mass spectrometry. , 2011, Journal of chromatography. A.

[54]  Kiyoshi Toko,et al.  Advanced Taste Sensors Based on Artificial Lipids with Global Selectivity to Basic Taste Qualities and High Correlation to Sensory Scores , 2010, Sensors.

[55]  B. Park,et al.  Choice of neighbor order in nearest-neighbor classification , 2008, 0810.5276.

[56]  Alexander J. Smola,et al.  Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.

[57]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[58]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[59]  Jie Xu,et al.  Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review , 2020 .

[60]  Walid Cherif,et al.  Optimization of K-NN algorithm by clustering and reliability coefficients: application to breast-cancer diagnosis , 2018 .

[61]  L. Breiman Random Forests , 2001, Machine Learning.