Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells
To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) mor...
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| Veröffentlicht in: | Scientific reports Jg. 12; H. 1; S. 11180 - 10 |
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01.07.2022
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| Abstract | To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods. |
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| AbstractList | To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods. Abstract To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods. To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods.To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods. |
| ArticleNumber | 11180 |
| Author | Miner, Jeffrey N. Lo, Yu-Hwa Joshi, Vaidehi Subramanian, Ramkumar Tang, Rui Zhang, Zunming |
| Author_xml | – sequence: 1 givenname: Ramkumar surname: Subramanian fullname: Subramanian, Ramkumar organization: Department of Electrical and Computer Engineering, University of California San Diego – sequence: 2 givenname: Rui surname: Tang fullname: Tang, Rui organization: Department of Electrical and Computer Engineering, University of California San Diego – sequence: 3 givenname: Zunming surname: Zhang fullname: Zhang, Zunming organization: Department of Electrical and Computer Engineering, University of California San Diego – sequence: 4 givenname: Vaidehi surname: Joshi fullname: Joshi, Vaidehi organization: Viscient Biosciences Inc – sequence: 5 givenname: Jeffrey N. surname: Miner fullname: Miner, Jeffrey N. organization: Viscient Biosciences Inc – sequence: 6 givenname: Yu-Hwa orcidid: 0000-0003-4602-1627 surname: Lo fullname: Lo, Yu-Hwa email: ylo@ucsd.edu organization: Department of Electrical and Computer Engineering, University of California San Diego |
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| Cites_doi | 10.1038/s41467-019-11984-2 10.1038/s41598-018-20166-x 10.1038/s41598-021-01951-7 10.1016/j.cgh.2019.12.025 10.1063/5.0024151 10.1136/flgastro-2013-100403 10.4254/wjh.v10.i2.231 10.1097/MCG.0000000000001284 10.1038/s41598-017-04151-4 10.1016/j.jhep.2019.02.012 10.3389/fphar.2020.603926 10.21037/tgh.2020.04.01 10.3390/cells9041005 10.1186/s12943-019-1043-x 10.1038/s41551-020-0569-y 10.1371/journal.pone.0212110 10.14218/JCTH.2020.00015 10.1186/s13550-015-0151-x 10.1093/jamia/ocab003 10.1371/journal.pone.0240867 10.1038/s41598-019-54904-6 10.3390/diagnostics11061078 10.1038/s41591-019-0660-7 10.1002/hep4.1450 10.3389/fmed.2021.615978 10.1038/labinvest.2015.95 10.1038/s41374-019-0315-9 10.1371/journal.pmed.1003149 10.1364/OPTICA.6.001297 10.3233/IDA-2002-6504 10.1038/s41598-020-58059-7 10.1038/s41598-020-79139-8 10.1109/BIBE50027.2020.00166 |
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| References | De Rudder (CR15) 2020; 100 Kostrzewski (CR40) 2020; 4 Ægidius (CR4) 2020; 10 Piazzolla, Mangia (CR8) 2020; 9 Gallegos-Orozco, Unzueta (CR11) 2013; 2 Balakrishnan, Loomba (CR12) 2020; 54 Peng, Stewart, Woodman, Ritchie, Qin (CR14) 2020; 11 Brunt (CR33) 2015; 1 CR18 Mancini (CR17) 2018; 10 Han, Lo (CR25) 2015; 5 Dyson, Anstee, McPherson (CR10) 2014; 5 Wang, Peng (CR32) 2021; 12 Duriez, Jacquet, Hoet, Roche, Bock, Rocher (CR38) 2020; 8 CR30 Ströbel (CR39) 2021; 11 Forlano (CR22) 2020; 18 Jain (CR3) 2021; 6 Furuta, Guo, Hirsova, Ibrahim (CR34) 2020; 9 Segovia-Miranda (CR5) 2019; 25 Tang (CR29) 2020; 5 Thoma (CR37) 2019; 2019 Popa (CR41) 2021; 11 Li, He, Guo, Chen, Shan (CR2) 2015; 5 Heinemann, Birk, Stierstorfer (CR7) 2019; 9 Löfstedt, Brynolfsson, Asklund, Nyholm, Garpebring (CR27) 2019; 14 Miyao (CR35) 2015; 95 Atabaki-Pasdar (CR21) 2020; 17 Salarian (CR6) 2019; 10 Heyens, Busschots, Koek, Robaeys, Francque (CR9) 2021; 8 Perveen, Shahbaz, Keshavjee, Guergachi (CR23) 2018; 8 Hammoutene, Rautou (CR36) 2019; 70 Wang (CR1) 2021; 11 Docherty (CR19) 2021; 28 Han (CR24) 2019; 6 Brynolfsson (CR28) 2017; 7 CR42 Kim (CR16) 2021; 11 Saif (CR13) 2020; 4 Sorino (CR20) 2020; 15 Ye, Ling, Zheng, Xu (CR31) 2019; 18 Japkowicz, Stephen (CR26) 2002; 6 HM Ægidius (15364_CR4) 2020; 10 S Ströbel (15364_CR39) 2021; 11 M De Rudder (15364_CR15) 2020; 100 15364_CR30 ZY Wang (15364_CR1) 2021; 11 M Docherty (15364_CR19) 2021; 28 D Li (15364_CR2) 2015; 5 EM Brunt (15364_CR33) 2015; 1 LJM Heyens (15364_CR9) 2021; 8 Y Han (15364_CR25) 2015; 5 M Salarian (15364_CR6) 2019; 10 N Atabaki-Pasdar (15364_CR21) 2020; 17 M Duriez (15364_CR38) 2020; 8 T Kostrzewski (15364_CR40) 2020; 4 C Peng (15364_CR14) 2020; 11 T Löfstedt (15364_CR27) 2019; 14 K Furuta (15364_CR34) 2020; 9 D Jain (15364_CR3) 2021; 6 TH Kim (15364_CR16) 2021; 11 S Perveen (15364_CR23) 2018; 8 JK Dyson (15364_CR10) 2014; 5 F Heinemann (15364_CR7) 2019; 9 15364_CR42 R Forlano (15364_CR22) 2020; 18 SL Popa (15364_CR41) 2021; 11 XK Wang (15364_CR32) 2021; 12 N Japkowicz (15364_CR26) 2002; 6 VA Piazzolla (15364_CR8) 2020; 9 E Thoma (15364_CR37) 2019; 2019 Q Ye (15364_CR31) 2019; 18 M Mancini (15364_CR17) 2018; 10 15364_CR18 R Tang (15364_CR29) 2020; 5 P Sorino (15364_CR20) 2020; 15 F Segovia-Miranda (15364_CR5) 2019; 25 M Balakrishnan (15364_CR12) 2020; 54 Y Han (15364_CR24) 2019; 6 P Brynolfsson (15364_CR28) 2017; 7 J Gallegos-Orozco (15364_CR11) 2013; 2 M Miyao (15364_CR35) 2015; 95 M Saif (15364_CR13) 2020; 4 A Hammoutene (15364_CR36) 2019; 70 |
| References_xml | – volume: 10 start-page: 1 year: 2019 end-page: 14 ident: CR6 article-title: Early detection and staging of chronic liver diseases with a protein MRI contrast agent publication-title: Nat. Commun. doi: 10.1038/s41467-019-11984-2 – volume: 8 start-page: 1 year: 2018 end-page: 12 ident: CR23 article-title: A systematic machine learning based approach for the diagnosis of non-alcoholic fatty liver disease risk and progression publication-title: Sci. Rep. doi: 10.1038/s41598-018-20166-x – volume: 11 start-page: 1 year: 2021 end-page: 18 ident: CR39 article-title: OPEN A 3D primary human cell-based in vitro model of non-alcoholic steatohepatitis for efficacy testing of clinical drug candidates publication-title: Sci. Rep. doi: 10.1038/s41598-021-01951-7 – ident: CR18 – volume: 1 start-page: 1 year: 2015 end-page: 22 ident: CR33 article-title: Non-alcoholic fatty liver disease publication-title: Nat. Rev. Dis. Prim. – volume: 2 start-page: 8 year: 2013 ident: CR11 article-title: Noninvasive diagnosis of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis publication-title: Oncol. Gastroenterol. Hepatol. Rep. – volume: 18 start-page: 2081 year: 2020 end-page: 2090.e9 ident: CR22 article-title: High-throughput, machine learning-based quantification of steatosis, inflammation, ballooning, and fibrosis in biopsies from patients with nonalcoholic fatty liver disease publication-title: Clin. Gastroenterol. Hepatol. doi: 10.1016/j.cgh.2019.12.025 – volume: 5 start-page: 126105 year: 2020 ident: CR29 article-title: 3D side-scattering imaging flow cytometer and convolutional neural network for label-free cell analysis publication-title: APL Photonics doi: 10.1063/5.0024151 – ident: CR30 – volume: 5 start-page: 211 year: 2014 end-page: 218 ident: CR10 article-title: Non-alcoholic fatty liver disease: a practical approach to diagnosis and staging publication-title: Frontline Gastroenterol. doi: 10.1136/flgastro-2013-100403 – volume: 10 start-page: 231 year: 2018 end-page: 245 ident: CR17 article-title: Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research publication-title: World J. Hepatol. doi: 10.4254/wjh.v10.i2.231 – volume: 54 start-page: 107 year: 2020 end-page: 113 ident: CR12 article-title: The role of noninvasive tests for differentiating NASH from NAFL and diagnosing advanced fibrosis among patients with NAFLD publication-title: J. Clin. Gastroenterol. doi: 10.1097/MCG.0000000000001284 – volume: 7 start-page: 1 year: 2017 end-page: 11 ident: CR28 article-title: Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters publication-title: Sci. Rep. doi: 10.1038/s41598-017-04151-4 – volume: 70 start-page: 1278 year: 2019 end-page: 1291 ident: CR36 article-title: Role of liver sinusoidal endothelial cells in non-alcoholic fatty liver disease publication-title: J. Hepatol. doi: 10.1016/j.jhep.2019.02.012 – volume: 11 start-page: 603926 year: 2020 ident: CR14 article-title: Non-alcoholic steatohepatitis: A review of its mechanism, models medical treatments publication-title: Front. Pharmacol. doi: 10.3389/fphar.2020.603926 – ident: CR42 – volume: 5 start-page: 1 year: 2015 end-page: 10 ident: CR25 article-title: Imaging cells in flow cytometer using spatial-temporal transformation publication-title: Sci. Rep. – volume: 6 start-page: 1 year: 2021 end-page: 21 ident: CR3 article-title: Evolution of the liver biopsy and its future publication-title: Transl. Gastroenterol. Hepatol. doi: 10.21037/tgh.2020.04.01 – volume: 9 start-page: 1005 year: 2020 ident: CR8 article-title: Noninvasive diagnosis of NAFLD and NASH publication-title: Cells doi: 10.3390/cells9041005 – volume: 18 start-page: 1 year: 2019 end-page: 13 ident: CR31 article-title: Liquid biopsy in hepatocellular carcinoma: Circulating tumor cells and circulating tumor DNA publication-title: Mol. Cancer doi: 10.1186/s12943-019-1043-x – volume: 4 start-page: 801 year: 2020 end-page: 813 ident: CR13 article-title: Noninvasive monitoring of chronic liver disease via near and shortwave-infrared imaging of endogenous lipofuscin HHS Public Access Author manuscript publication-title: Nat. Biomed. Eng. doi: 10.1038/s41551-020-0569-y – volume: 14 start-page: 1 year: 2019 end-page: 18 ident: CR27 article-title: Gray-level invariant Haralick texture features publication-title: PLoS One doi: 10.1371/journal.pone.0212110 – volume: 11 start-page: 1 year: 2021 end-page: 15 ident: CR1 article-title: Single-cell and bulk transcriptomics of the liver reveals potential targets of NASH with fibrosis publication-title: Sci. Rep. – volume: 8 start-page: 359 issue: 4 year: 2020 end-page: 370 ident: CR38 article-title: A 3D human liver model of non-alcoholic steatohepatitis publication-title: J. Clin. Transl. Hepatol. doi: 10.14218/JCTH.2020.00015 – volume: 5 start-page: 1 year: 2015 end-page: 10 ident: CR2 article-title: Targeting activated hepatic stellate cells (aHSCs) for liver fibrosis imaging publication-title: EJNMMI Res. doi: 10.1186/s13550-015-0151-x – volume: 28 start-page: 1235 year: 2021 end-page: 1241 ident: CR19 article-title: Development of a novel machine learning model to predict presence of non-alcoholic steatohepatitis publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocab003 – volume: 15 start-page: 1 year: 2020 end-page: 15 ident: CR20 article-title: Selecting the best machine learning algorithm to support the diagnosis of non-alcoholic fatty liver disease: A meta learner study publication-title: PLoS One doi: 10.1371/journal.pone.0240867 – volume: 2019 start-page: 61 year: 2019 end-page: 66 ident: CR37 article-title: Evolving models for NASH drug discovery publication-title: Therapeutics – volume: 9 start-page: 1 year: 2019 end-page: 10 ident: CR7 article-title: Deep learning enables pathologist-like scoring of NASH models publication-title: Sci. Rep. doi: 10.1038/s41598-019-54904-6 – volume: 9 start-page: 1 year: 2020 end-page: 19 ident: CR34 article-title: Emerging roles of liver sinusoidal endothelial cells in non-alcoholic steatohepatitis publication-title: Biology (Basel). – volume: 11 start-page: 1 year: 2021 end-page: 22 ident: CR41 article-title: Non-alcoholic fatty liver disease: Implementing complete automated diagnosis and staging a systematic review publication-title: Diagnostics doi: 10.3390/diagnostics11061078 – volume: 25 start-page: 1885 year: 2019 end-page: 1893 ident: CR5 article-title: Three-dimensional spatially resolved geometrical and functional models of human liver tissue reveal new aspects of NAFLD progression publication-title: Nat. Med. doi: 10.1038/s41591-019-0660-7 – volume: 4 start-page: 77 year: 2020 end-page: 91 ident: CR40 article-title: A microphysiological system for studying nonalcoholic steatohepatitis publication-title: Hepatol. Commun. doi: 10.1002/hep4.1450 – volume: 8 start-page: 1 year: 2021 end-page: 20 ident: CR9 article-title: Liver fibrosis in non-alcoholic fatty liver disease: From liver biopsy to non-invasive biomarkers in diagnosis and treatment publication-title: Front. Med. doi: 10.3389/fmed.2021.615978 – volume: 95 start-page: 1130 year: 2015 end-page: 1144 ident: CR35 article-title: Pivotal role of liver sinusoidal endothelial cells in NAFLD/NASH progression publication-title: Lab. Investig. doi: 10.1038/labinvest.2015.95 – volume: 100 start-page: 147 year: 2020 end-page: 160 ident: CR15 article-title: Automated computerized image analysis for the user-independent evaluation of disease severity in pre-clinical models of NAFLD/NASH publication-title: Lab. Investig. doi: 10.1038/s41374-019-0315-9 – volume: 11 start-page: 1 year: 2021 end-page: 9 ident: CR16 article-title: Circulating miRNA is a useful diagnostic biomarker for nonalcoholic steatohepatitis in nonalcoholic fatty liver disease publication-title: Sci. Rep. – volume: 17 start-page: 1 year: 2020 end-page: 27 ident: CR21 article-title: Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts publication-title: PLoS Med. doi: 10.1371/journal.pmed.1003149 – volume: 6 start-page: 1297 year: 2019 ident: CR24 article-title: Cameraless high-throughput three-dimensional imaging flow cytometry publication-title: Optica doi: 10.1364/OPTICA.6.001297 – volume: 6 start-page: 429 year: 2002 end-page: 449 ident: CR26 article-title: The class imbalance problem: A systematic study publication-title: Intell. Data Anal. doi: 10.3233/IDA-2002-6504 – volume: 12 start-page: 1 year: 2021 end-page: 16 ident: CR32 article-title: Targeting liver sinusoidal endothelial cells: An attractive therapeutic strategy to control inflammation in nonalcoholic fatty liver disease publication-title: Front. Pharmacol. – volume: 10 start-page: 1 year: 2020 end-page: 12 ident: CR4 article-title: Multi-omics characterization of a diet-induced obese model of non-alcoholic steatohepatitis publication-title: Sci. Rep. doi: 10.1038/s41598-020-58059-7 – volume: 25 start-page: 1885 year: 2019 ident: 15364_CR5 publication-title: Nat. Med. doi: 10.1038/s41591-019-0660-7 – volume: 10 start-page: 1 year: 2019 ident: 15364_CR6 publication-title: Nat. Commun. doi: 10.1038/s41467-019-11984-2 – volume: 7 start-page: 1 year: 2017 ident: 15364_CR28 publication-title: Sci. Rep. doi: 10.1038/s41598-017-04151-4 – volume: 6 start-page: 429 year: 2002 ident: 15364_CR26 publication-title: Intell. Data Anal. doi: 10.3233/IDA-2002-6504 – volume: 10 start-page: 1 year: 2020 ident: 15364_CR4 publication-title: Sci. Rep. doi: 10.1038/s41598-020-58059-7 – volume: 18 start-page: 1 year: 2019 ident: 15364_CR31 publication-title: Mol. Cancer doi: 10.1186/s12943-019-1043-x – volume: 11 start-page: 1 year: 2021 ident: 15364_CR1 publication-title: Sci. Rep. doi: 10.1038/s41598-020-79139-8 – volume: 5 start-page: 1 year: 2015 ident: 15364_CR2 publication-title: EJNMMI Res. doi: 10.1186/s13550-015-0151-x – volume: 2019 start-page: 61 year: 2019 ident: 15364_CR37 publication-title: Therapeutics – volume: 11 start-page: 1 year: 2021 ident: 15364_CR39 publication-title: Sci. Rep. doi: 10.1038/s41598-021-01951-7 – volume: 5 start-page: 126105 year: 2020 ident: 15364_CR29 publication-title: APL Photonics doi: 10.1063/5.0024151 – volume: 9 start-page: 1 year: 2020 ident: 15364_CR34 publication-title: Biology (Basel). – volume: 70 start-page: 1278 year: 2019 ident: 15364_CR36 publication-title: J. Hepatol. doi: 10.1016/j.jhep.2019.02.012 – volume: 4 start-page: 77 year: 2020 ident: 15364_CR40 publication-title: Hepatol. Commun. doi: 10.1002/hep4.1450 – volume: 9 start-page: 1005 year: 2020 ident: 15364_CR8 publication-title: Cells doi: 10.3390/cells9041005 – ident: 15364_CR42 doi: 10.1109/BIBE50027.2020.00166 – volume: 18 start-page: 2081 year: 2020 ident: 15364_CR22 publication-title: Clin. Gastroenterol. Hepatol. doi: 10.1016/j.cgh.2019.12.025 – volume: 8 start-page: 1 year: 2018 ident: 15364_CR23 publication-title: Sci. Rep. doi: 10.1038/s41598-018-20166-x – volume: 54 start-page: 107 year: 2020 ident: 15364_CR12 publication-title: J. Clin. Gastroenterol. doi: 10.1097/MCG.0000000000001284 – volume: 17 start-page: 1 year: 2020 ident: 15364_CR21 publication-title: PLoS Med. doi: 10.1371/journal.pmed.1003149 – ident: 15364_CR18 – volume: 6 start-page: 1297 year: 2019 ident: 15364_CR24 publication-title: Optica doi: 10.1364/OPTICA.6.001297 – volume: 11 start-page: 1 year: 2021 ident: 15364_CR16 publication-title: Sci. Rep. doi: 10.1038/s41598-020-79139-8 – volume: 4 start-page: 801 year: 2020 ident: 15364_CR13 publication-title: Nat. Biomed. Eng. doi: 10.1038/s41551-020-0569-y – volume: 14 start-page: 1 year: 2019 ident: 15364_CR27 publication-title: PLoS One doi: 10.1371/journal.pone.0212110 – volume: 95 start-page: 1130 year: 2015 ident: 15364_CR35 publication-title: Lab. Investig. doi: 10.1038/labinvest.2015.95 – volume: 2 start-page: 8 year: 2013 ident: 15364_CR11 publication-title: Oncol. Gastroenterol. Hepatol. Rep. – volume: 8 start-page: 359 issue: 4 year: 2020 ident: 15364_CR38 publication-title: J. Clin. Transl. Hepatol. doi: 10.14218/JCTH.2020.00015 – volume: 5 start-page: 1 year: 2015 ident: 15364_CR25 publication-title: Sci. Rep. – volume: 10 start-page: 231 year: 2018 ident: 15364_CR17 publication-title: World J. Hepatol. doi: 10.4254/wjh.v10.i2.231 – volume: 28 start-page: 1235 year: 2021 ident: 15364_CR19 publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocab003 – volume: 8 start-page: 1 year: 2021 ident: 15364_CR9 publication-title: Front. Med. doi: 10.3389/fmed.2021.615978 – volume: 12 start-page: 1 year: 2021 ident: 15364_CR32 publication-title: Front. Pharmacol. – volume: 9 start-page: 1 year: 2019 ident: 15364_CR7 publication-title: Sci. Rep. doi: 10.1038/s41598-019-54904-6 – volume: 11 start-page: 603926 year: 2020 ident: 15364_CR14 publication-title: Front. Pharmacol. doi: 10.3389/fphar.2020.603926 – volume: 1 start-page: 1 year: 2015 ident: 15364_CR33 publication-title: Nat. Rev. Dis. Prim. – volume: 11 start-page: 1 year: 2021 ident: 15364_CR41 publication-title: Diagnostics doi: 10.3390/diagnostics11061078 – volume: 5 start-page: 211 year: 2014 ident: 15364_CR10 publication-title: Frontline Gastroenterol. doi: 10.1136/flgastro-2013-100403 – volume: 100 start-page: 147 year: 2020 ident: 15364_CR15 publication-title: Lab. Investig. doi: 10.1038/s41374-019-0315-9 – volume: 6 start-page: 1 year: 2021 ident: 15364_CR3 publication-title: Transl. Gastroenterol. Hepatol. doi: 10.21037/tgh.2020.04.01 – volume: 15 start-page: 1 year: 2020 ident: 15364_CR20 publication-title: PLoS One doi: 10.1371/journal.pone.0240867 – ident: 15364_CR30 |
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| Title | Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells |
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