scholarly journals Meta-Analysis: Urinary Calprotectin for Discrimination of Intrinsic and Prerenal Acute Kidney Injury

2019 ◽  
Vol 8 (1) ◽  
pp. 74 ◽  
Author(s):  
Jia-Jin Chen ◽  
Pei-Chun Fan ◽  
George Kou ◽  
Su-Wei Chang ◽  
Yi-Ting Chen ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Pediatric Population ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Kidney Injury ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Significant Difference

Background: Urinary calprotectin is a novel biomarker that distinguishes between intrinsic or prerenal acute kidney injury (AKI) in different studies. However, these studies were based on different populations and different AKI criteria. We evaluated the diagnostic accuracy of urinary calprotectin and compared its diagnostic performance in different AKI criteria and study populations. Method: In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched PubMed, Embase, and the Cochrane database up to September 2018. The diagnostic performance of urinary calprotectin (sensitivity, specificity, predictive ratio, and cutoff point) was extracted and evaluated. Result: This study included six studies with a total of 502 patients. The pooled sensitivity and specificity were 0.90 and 0.93, respectively. The pooled positive likelihood ratio (LR) was 15.15, and the negative LR was 0.11. The symmetric summary receiver operating characteristic (symmetric SROC) with pooled diagnostic accuracy was 0.9667. The relative diagnostic odds ratio (RDOC) of the adult to pediatric population and RDOCs of different acute kidney injury criteria showed no significant difference in their diagnostic accuracy. Conclusion: Urinary calprotectin is a good diagnostic tool for the discrimination of intrinsic and prerenal AKI under careful inspection after exclusion of urinary tract infection and urogenital malignancies. Its performance is not affected by different AKI criteria and adult or pediatric populations.

The Accuracy of Urinary TIMP-2 and IGFBP7 for the Diagnosis of Cardiac Surgery-Associated Acute Kidney Injury: A Systematic Review and Meta-Analysis

2018 ◽  
Vol 35 (10) ◽  
pp. 1013-1025 ◽  
Author(s):  
Qiang Tai ◽  
Huimin Yi ◽  
Xuxia Wei ◽  
Wenfeng Xie ◽  
Ou Zeng ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Data Extraction ◽  
Meta Analysis ◽  
Positive Likelihood Ratio ◽  
Kidney Injury ◽  
Diagnostic Odds Ratio ◽  
Tissue Inhibitor Of Metalloproteinase ◽  
Summary Receiver Operating Characteristic ◽  
The Stability

Background: Tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) are recent promising markers for identification of cardiac surgery-associated acute kidney injury (CSA-AKI). The aim of this study was systematically and quantitatively to evaluate the accuracy of urinary TIMP-2 and IGFBP7 for the diagnosis of CSA-AKI. Methods: Three databases including PubMed, ISI web of knowledge, and Embase were systematically searched from inception to March 2018. Two investigators conducted the processes of literature search study selection, data extraction, and quality evaluation independently. Meta-DiSc and STATA were used for all statistical analyses. Results: A total of 8 studies comprising 552 patients were included in this meta-analysis. Pooled sensitivity and specificity with corresponding 95% confidence intervals (CIs) were 0.79 (95% CI, 0.71-0.86, I 2 = 74.2%) and 0.76 (95% CI, 0.72-0.80, I 2 = 80.8%), respectively. Pooled positive likelihood ratio (LR), negative LR, and diagnostic odds ratio were 3.49 (95% CI, 2.44-5.00, I 2 = 61.5%), 0.31(95% CI, 0.19-0.51, I 2 = 51.8%), and 14.89 (95% CI, 7.31-30.32, I 2 = 27.9%), respectively. The area under curve estimated by summary receiver operating characteristic was 0.868 (standard error [SE] 0.032) with a Q* value of 0.799 (SE 0.032). Sensitivity analysis demonstrated that one study notably affected the stability of pooled results. One of the subgroups investigated—AKI threshold—could account for partial heterogeneity. Conclusion: Urinary TIMP-2 and IGFBP7 is a helpful biomarker for early diagnosis of CSA-AKI. And, the potential of this biomarker with a broader spectrum of clinical settings may be the focus of future studies.

scholarly journals Furosemide stress test as a predictive marker of acute kidney injury progression or renal replacement therapy: a systemic review and meta-analysis

2020 ◽  
Author(s):  
Jia-Jin Chen ◽  
Chih-Hsiang Chang ◽  
Yen Ta Huang ◽  
George Kuo
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Diagnostic Accuracy ◽  
Replacement Therapy ◽  
Sensitivity And Specificity ◽  
Odds Ratio ◽  
Diagnostic Performance ◽  
Stress Test ◽  
Kidney Injury ◽  
Diagnostic Odds Ratio

Abstract Background: The use of the furosemide stress test (FST) as an acute kidney injury (AKI) severity marker has been described in several trials. However, the diagnostic performance of the FST in predicting AKI progression has not yet been fully discussed. Methods: In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched the PubMed, Embase, Cochrane databases up to March, 2020. The diagnostic performance of the FST (in terms of sensitivity, specificity, number of events, true positive, false positive) was extracted and evaluated. Results: We identified eleven trials that enrolled a total of 1366 patients, including 517 patients and 1017 patients for whom the outcomes in terms of AKI stage progression and renal replacement therapy (RRT), respectively, were reported. The pooled sensitivity and specificity results of the FST for AKI progression prediction were 0.81 (95% CI: 0.74 - 0.87) and 0.88 (95% CI: 0.82- 0.92), respectively. The pooled positive likelihood ratio (LR) was 5.45 (95% CI: 3.96-7.50), the pooled negative LR was 0.26 (95% CI: 0.19-0.36), and the pooled diagnostic odds ratio (DOR) was 29.69 (95% CI: 17.00-51.85). The summary receiver operating characteristics (SROC) with pooled diagnostic accuracy was 0.88. The diagnostic performance of the FST in predicting AKI progression was not affected by different AKI criteria or underlying chronic kidney disease. The pooled sensitivity and specificity results of the FST for RRT prediction were 0.84 (95% CI: 0.72-0.91) and 0.77 (95% CI: 0.64-0.87), respectively. The pooled positive LR and pooled negative LR were 3.16 (95% CI: 2.06-4.86) and 0.25 (95% CI: 0.14-0.44), respectively. The pooled diagnostic odds ratio (DOR) was 13.59 (95% CI: 5.74-32.17) and SROC with pooled diagnostic accuracy was 0.86. The diagnostic performance of FST for RRT prediction is better in stage 1-2 AKI comparing to stage 3 AKI (relative DOR: 5.75, 95% CI: 2.51-13.33) Conclusion: The FST is a simple tool for the identification of AKI populations at high risk of AKI progression and the need for RRT and the diagnostic performance of FST in RRT prediction is better in early AKI population.

scholarly journals Furosemide stress test as a predictive marker of acute kidney injury progression or renal replacement therapy: a systemic review and meta-analysis

2020 ◽  
Author(s):  
Jia-Jin Chen ◽  
Chih-Hsiang Chang ◽  
Yen Ta Huang ◽  
George Kuo
Keyword(s):  
Acute Kidney Injury ◽  
Renal Replacement Therapy ◽  
Diagnostic Accuracy ◽  
Replacement Therapy ◽  
Sensitivity And Specificity ◽  
Odds Ratio ◽  
Diagnostic Performance ◽  
Stress Test ◽  
Kidney Injury ◽  
Diagnostic Odds Ratio

Abstract Background The use of the furosemide stress test (FST) as an acute kidney injury (AKI) severity marker has been discussed in several different trials. However, the diagnostic performance of the FST in predicting AKI progression has not yet been fully discussed. Methods In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched the PubMed, Embase, MEDLINE and Cochrane databases up to December, 31 2019. The diagnostic performance of the FST (in terms of sensitivity, specificity, number of events, number of true positives, and number of false positives) was extracted and evaluated. Results We identified nine trials that enrolled a total of 1296 patients, including 432 patients and 864 patients for whom the outcomes in terms of AKI stage progression and renal replacement therapy (RRT), respectively, were reported. The pooled sensitivity and specificity results of the FST for AKI progression prediction were 0.83 (95% CI: 0.76 - 0.89) and 0.87 (95% CI: 0.80 - 0.92), respectively. The pooled positive likelihood ratio (LR) was 5.27 (95% CI: 3.75-7.39), the pooled negative LR was 0.22 (95% CI: 0.15 - 0.32), and the pooled diagnostic odds ratio (DOR) was 29.34 (95% CI: 16.35-52.66). The summary receiver operating characteristics (SROC) with pooled diagnostic accuracy was 0.87. The diagnostic performance of the FST in predicting AKI progression was not affected by different AKI criteria (relative DOR: 1.04, 95% CI: 0.18 - 5.94) or underlying chronic kidney disease (relative DOR: 0.66, 95% CI: 0.08 - 5.70). The pooled sensitivity and specificity results of the FST for RRT prediction were 0.87 (95% CI: 0.76 - 0.93) and 0.71(95% CI: 0.56 -0.83), respectively. The pooled positive LR and pooled negative LR were 2.85 (95% CI: 1.81-4.48) and 0.22(95% CI: 0.11- 0.43), respectively. The pooled diagnostic odds ratio (DOR) was 13.36 (95% CI: 4.79-37.27) and SROC with pooled diagnostic accuracy was 0.87. Conclusion The FST is a simple tool for the identification of AKI populations at high risk of AKI progression, but the diagnostic performance of FST in RRT prediction is suboptimal.

scholarly journals Meta-Analysis of microRNAs as Potential Biomarkers for Detecting Esophageal Carcinoma in Asian Populations

2017 ◽  
Vol 32 (4) ◽  
pp. 375-383 ◽  
Author(s):  
Mei Li ◽  
Fei Wu ◽  
Yu Ji ◽  
Lan Yang ◽  
Feng Li
Keyword(s):  
Esophageal Carcinoma ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Healthy Controls ◽  
Summary Receiver Operating Characteristic ◽  
Significant Difference

Background An Increasing number of studies in the literature have shown that microRNAs (miRNAs) can be used as early diagnostic markers for esophageal carcinoma (EC), but their conclusions remain controversial. Hence, we performed this meta-analysis to evaluate the diagnostic accuracy of using miRNAs in EC and to provide an experimental basis for early diagnosis of the disease. Methods This meta-analysis included 39 Asian studies from 18 articles, which covered 3,708 EC patients and 2,689 healthy controls. We used a bivariate random-effects model, the chi-square test and the I2 test to assess sensitivity and heterogeneity. Results Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio of miRNAs for diagnosis of EC in Asians reached 0.798, 0.785, 3.705, 0.257 and 14.391, respectively. Additionally, the area under the summary receiver operating characteristic curve was 0.86. Subgroup analysis based on research country (China vs. Japan), sample types (plasma vs. serum) and miRNAs (single vs. multiple; singly reported miRNAs vs. repeatedly reported miRNAs) showed no significant difference in accuracy of diagnosis for each subgroup. Conclusions MiRNAs can distinguish EC patients from healthy controls. Blood-based miRNAs have better diagnostic value in detecting EC than saliva-based miRNAs, whereas both serum and plasma are recommended for clinical specimens for miRNA detection.

scholarly journals The Potential Diagnostic Accuracy of Circulating MicroRNAs for Leukemia: A Meta-Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110119
Author(s):  
Wen-Ting Zhang ◽  
Guo-Xun Zhang ◽  
Shuai-Shuai Gao
Keyword(s):  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Subgroup Analysis ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Diagnostic Odds Ratio ◽  
Circulating Micrornas ◽  
Sensitivity Specificity

Background: Leukemia is a common malignant disease in the human blood system. Many researchers have proposed circulating microRNAs as biomarkers for the diagnosis of leukemia. We conducted a meta-analysis to evaluate the diagnostic accuracy of circulating miRNAs in the diagnosis of leukemia. Methods: A comprehensive literature search (updated to October 13, 2020) in PubMed, EMBASE, Web of Science, Cochrane Library, Wanfang database and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for diagnosing leukemia were pooled for both overall and subgroup analysis. The meta-regression and subgroup analysis were performed to explore heterogeneity and Deeks’ funnel plot was used to assess publication bias. Results: 49 studies from 22 publications with a total of 3,489 leukemia patients and 2,756 healthy controls were included in this meta-analysis. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio and area under the curve were 0.83, 0.92, 10.8, 0.18, 59 and 0.94, respectively. Subgroup analysis shows that the microRNA clusters of plasma type could carry out a better diagnostic accuracy of leukemia patients. In addition, publication bias was not found. Conclusions: Circulating microRNAs can be used as a promising noninvasive biomarker in the early diagnosis of leukemia.

scholarly journals Diagnostic Accuracy of Machine Learning-Based Radiomics in Grading Gliomas: Systematic Review and Meta-Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Curtis K. Sohn ◽  
Sotirios Bisdas
Keyword(s):  
Machine Learning ◽  
Diagnostic Accuracy ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Total Sample ◽  
Low Grade ◽  
Sample Sizes ◽  
Summary Receiver Operating Characteristic ◽  
Pubmed Database ◽  
Sensitivity Specificity

Purpose. This study aimed to estimate the diagnostic accuracy of machine learning- (ML-) based radiomics in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG) and to identify potential covariates that could affect the diagnostic accuracy of ML-based radiomic analysis in classifying gliomas. Method. A primary literature search of the PubMed database was conducted to find all related literatures in English between January 1, 2009, and May 1, 2020, with combining synonyms for “machine learning,” “glioma,” and “radiomics.” Five retrospective designed original articles including LGG and HGG subjects were chosen. Pooled sensitivity, specificity, their 95% confidence interval, area under curve (AUC), and hierarchical summary receiver-operating characteristic (HSROC) models were obtained. Result. The pooled sensitivity when diagnosing HGG was higher (96% (95% CI: 0.93, 0.98)) than the specificity when diagnosing LGG (90% (95% CI 0.85, 0.93)). Heterogeneity was observed in both sensitivity and specificity. Metaregression confirmed the heterogeneity in sample sizes ( p = 0.05 ), imaging sequence types ( p = 0.02 ), and data sources ( p = 0.01 ), but not for the inclusion of the testing set ( p = 0.19 ), feature extraction number ( p = 0.36 ), and selection of feature number ( p = 0.18 ). The results of subgroup analysis indicate that sample sizes of more than 100 and feature selection numbers less than the total sample size positively affected the diagnostic performance in differentiating HGG from LGG. Conclusion. This study demonstrates the excellent diagnostic performance of ML-based radiomics in differentiating HGG from LGG.

scholarly journals K-rasMutational Status in Cytohistological Tissue as a Molecular Marker for the Diagnosis of Pancreatic Cancer: A Systematic Review and Meta-Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jing Yang ◽  
Jingjing Li ◽  
Rong Zhu ◽  
Huawei Zhang ◽  
Yuanyuan Zheng ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Diagnostic Accuracy ◽  
Test Performance ◽  
Meta Analysis ◽  
Diagnostic Odds Ratio ◽  
Pancreatic Tissue ◽  
Test Material ◽  
Original Research ◽  
Summary Receiver Operating Characteristic ◽  
Diagnostic Significance

Background. More clinically meaningful diagnostic tests are needed in pancreatic cancer (PC).K-rasmutations are the most frequently acquired genetic alteration.Methods. Original research articles involving the diagnostic accuracy ofK-rasmutation detection in PC were selected. Data were presented as forest plots and summary receiver operating characteristic (SROC) curve analysis was used to summarize the overall test performance.Results. We assessed 19 studies from 16 published articles. The reports were divided into three groups according to the process used to obtain the test material. The summary estimates for detectingK-rasstatus using an invasive method (fine needle aspiration (FNA), endoscopic retrograde cholangiopancreatography (ERCP), or surgery) were better than cytology: the pooled sensitivity was 77% (95% confidence interval (CI): 74–80%) versus 54% (95% CI: 47–61%); specificity was 88% (95% CI: 85–91%) versus 91% (95% CI: 83–96%); and diagnostic odds ratio (DOR) was 20.26 (11.40–36.03) versus 7.52 (95% CI: 2.80–20.18), respectively. When two procedures were combined, the diagnostic accuracy was markedly improved.Conclusions. The analysis ofK-rasmutations in pancreatic tissue has a promising diagnostic significance in PC. Further valuable studies are needed.

scholarly journals The Diagnostic Accuracy of HE4 in Lung Cancer: A Meta-Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Daye Cheng ◽  
Ying Sun ◽  
Hu He
Keyword(s):  
Lung Cancer ◽  
Diagnostic Accuracy ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Large Sample Size ◽  
Summary Receiver Operating Characteristic ◽  
Diagnosis Of Lung Cancer

The diagnostic value of serum HE4 in patients with lung cancer remains controversial. Thus, we performed a systematic review and meta-analysis to assess the diagnostic accuracy of serum HE4 for lung cancer. We conducted a comprehensive literature search in PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and WANFANG databases between Jan. 1966 and Nov. 2014. The diagnostic sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (SROC) were pooled by Meta-DiSc 1.4 software. A total of seven articles including 715 cases and 549 controls were included for analysis. The summary estimates for serum HE4 in the diagnosis of lung cancer in these studies were pooled SEN 0.72 (95% CI: 0.68–0.75), SPE 0.85 (95% CI: 0.81–0.88), PLR 4.68 (95% CI: 3.23–6.78), NLR 0.31 (95% CI: 0.24–0.39), and DOR 17.14 (95% CI: 9.72–30.20), and the area under the curve (AUC) was 0.8557. This meta-analysis indicated that serum HE4 is a potential tool in the diagnosis of lung cancer. In addition, considering the high heterogeneity and potential publication bias, further studies with rigorous design and large sample size are needed in the future.

Sensitivity and Specificity of Dickkopf-1 Protein in Serum for Diagnosing Hepatocellular Carcinoma: A Meta-Analysis

2014 ◽  
Vol 29 (4) ◽  
pp. 403-410 ◽  
Author(s):  
Jie Zhang ◽  
Ying Zhao ◽  
Qin Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Diagnostic Accuracy ◽  
Test Performance ◽  
Meta Analysis ◽  
Diagnostic Odds Ratio ◽  
Likelihood Ratios ◽  
Summary Receiver Operating Characteristic ◽  
Knowledge Infrastructure ◽  
Combined Test ◽  
Dickkopf 1

Objective This meta-analysis evaluated the diagnostic accuracy of positive serum Dickkopf-1 (DKK1) for diagnosing hepatocellular carcinoma (HCC). Material and methods Articles listed on Embase, PubMed, Wanfang, Weipu Periodical Database or the Chinese National Knowledge Infrastructure (CNKI) and published up to July 10, 2013, were searched in either English or Chinese. The pooled sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR) and summary receiver operating characteristic (sROC) curve were calculated to summarize the overall test performance. Results Four articles (6 studies) provided DKK1 diagnostic data. The pooled SEN, SPE, PLR, NLR, DOR and area under the sROC curve of DKK1 for the diagnosis of HCC were 0.65 (95% confidence interval [95% CI], 0.52-0.76), 0.94 (95% CI, 0.82-0.98), 10.1 (95% CI, 3.68-27.74), 0.38 (95% CI, 0.28-0.51), 26.90 (95% CI, 10.45-69.19) and 0.84 (95% CI, 0.81-0.87), respectively. Three articles (5 studies) provided DKK1 and α-fetoprotein (AFP) combined test data. The pooled SEN, SPE, PLR, NLR, DOR and area under the sROC curve of combined detection for the diagnosis of HCC were 0.81 (95% CI, 0.76-0.85), 0.85 (95% CI, 0.78-0.91), 5.52 (95% CI, 3.76-8.10), 0.22 (95% CI, 0.19-0.27), 24.60 (95% CI, 17.69-34.19) and 0.88 (95% CI, 0.85-0.91), respectively. Conclusion Both DKK1 and DKK1 plus AFP had high diagnostic accuracy for diagnosis of HCC.

scholarly journals Artificial Intelligence in Gastric Cancer: Identifying Gastric Cancer Using Endoscopic Images with Convolutional Neural Network

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5253
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Bruno Andreas Walther ◽  
Ming-Chin Lin ◽  
Yu-Chuan (Jack) Li
Keyword(s):  
Gastric Cancer ◽  
Likelihood Ratio ◽  
Meta Analysis ◽  
Characteristic Curve ◽  
Positive Likelihood Ratio ◽  
Negative Likelihood Ratio ◽  
Work Load ◽  
Diagnostic Odds Ratio ◽  
Summary Receiver Operating Characteristic ◽  
Sensitivity Specificity

Gastric cancer (GC) is one of the most newly diagnosed cancers and the fifth leading cause of death globally. Identification of early gastric cancer (EGC) can ensure quick treatment and reduce significant mortality. Therefore, we aimed to conduct a systematic review with a meta-analysis of current literature to evaluate the performance of the CNN model in detecting EGC. We conducted a systematic search in the online databases (e.g., PubMed, Embase, and Web of Science) for all relevant original studies on the subject of CNN in EGC published between January 1, 2010, and March 26, 2021. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the risk of bias. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Moreover, a summary receiver operating characteristic curve (SROC) was plotted. Of the 171 studies retrieved, 15 studies met inclusion criteria. The application of the CNN model in the diagnosis of EGC achieved a SROC of 0.95, with corresponding sensitivity of 0.89 (0.88–0.89), and specificity of 0.89 (0.89–0.90). Pooled sensitivity and specificity for experts endoscopists were 0.77 (0.76–0.78), and 0.92 (0.91–0.93), respectively. However, the overall SROC for the CNN model and expert endoscopists was 0.95 and 0.90. The findings of this comprehensive study show that CNN model exhibited comparable performance to endoscopists in the diagnosis of EGC using digital endoscopy images. Given its scalability, the CNN model could enhance the performance of endoscopists to correctly stratify EGC patients and reduce work load.

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