Critical Analysis of Risk Factors and Machine-Learning-Based Gastric Cancer Risk Prediction Models: A Systematic Review
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W. Miao | Rongrong Huang | Zeyu Fan | Ziju He
[1] Hongbing Shen,et al. Development, validation, and evaluation of a risk assessment tool for personalized screening of gastric cancer in Chinese populations , 2023, BMC Medicine.
[2] A. Olshan,et al. Discrimination between Precancerous Gastric Lesions and Gastritis Using a Gastric Cancer Risk Stratification Model , 2023, Asian Pacific journal of cancer prevention : APJCP.
[3] Helda Tutunchi,et al. Fruit and vegetable intake in relation to gastric cancer risk: A comprehensive and updated systematic review and dose-response meta-analysis of cohort studies , 2023, Frontiers in Nutrition.
[4] W. Miao,et al. Development and validation of an artificial neural network model for non-invasive gastric cancer screening and diagnosis , 2022, Scientific reports.
[5] Hao Yan,et al. Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview , 2022, World journal of gastroenterology.
[6] E. Tong,et al. Evaluation of Cancer Deaths Attributable to Tobacco in California, 2014-2019 , 2022, JAMA network open.
[7] Fa-Ming Yin,et al. Developing and validating nomograms for predicting the survival in patients with clinical local-advanced gastric cancer , 2022, Frontiers in Oncology.
[8] M. de Kamps,et al. Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools , 2022, Cancers.
[9] Hongbing Shen,et al. C-reactive protein and cancer risk: a pan-cancer study of prospective cohort and Mendelian randomization analysis , 2022, BMC Medicine.
[10] Q. Dong,et al. Prediction of gastric cancer risk by a polygenic risk score of Helicobacter pylori , 2022, World journal of gastrointestinal oncology.
[11] W. Niu,et al. Prediction of presurgical metabolic syndrome for gastric cancer‐specific mortality is more evident in smokers: The FIESTA study , 2022, Cancer medicine.
[12] Peiyuan Yin,et al. Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy , 2022, Frontiers in Immunology.
[13] F. Jiang,et al. Identification and Validation of an m6A Modification of JAK-STAT Signaling Pathway–Related Prognostic Prediction Model in Gastric Cancer , 2022, Frontiers in genetics.
[14] Cong Lin,et al. Identification of a 3-Gene Model as Prognostic Biomarker in Patients With Gastric Cancer , 2022, Frontiers in Oncology.
[15] Fanghai Han,et al. Immune-Related LncRNAs to Construct a Prognosis Risk-Assessment Model for Gastric Cancer , 2022, Current oncology.
[16] Yu Guang Wang,et al. Cell graph neural networks enable the precise prediction of patient survival in gastric cancer , 2022, npj Precision Oncology.
[17] Tao Wang,et al. A Deep Learning Quantification Algorithm for HER2 Scoring of Gastric Cancer , 2022, Frontiers in Neuroscience.
[18] Songbo Zhao,et al. Accuracy evaluation of combining gastroscopy, multi-slice spiral CT, Her-2, and tumor markers in gastric cancer staging diagnosis , 2022, World Journal of Surgical Oncology.
[19] P. Friedmann,et al. Serum Pepsinogen as a Biomarker for Gastric Cancer in the United States: A Nested Case-Control Study using the PLCO Cancer Screening Trial Data. , 2022, Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology.
[20] Shuhao Wang,et al. Assessment of deep learning assistance for the pathological diagnosis of gastric cancer , 2022, Modern Pathology.
[21] Dechun Liu,et al. A new risk model based on a 11-m6A-related lncRNA signature for predicting prognosis and monitoring immunotherapy for gastric cancer , 2022, BMC Cancer.
[22] Jana Schaich Borg,et al. Computational Ethics , 2022, HMD Praxis der Wirtschaftsinformatik.
[23] Lei Wu,et al. A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study , 2022, EClinicalMedicine.
[24] Y. Liu,et al. Establishing a cancer driver gene signature-based risk model for predicting the prognoses of gastric cancer patients , 2022, Aging.
[25] Jing Chen,et al. A novel immune-related lncRNA pair signature for prognostic prediction and immune response evaluation in gastric cancer: a bioinformatics and biological validation study , 2022, Cancer cell international.
[26] Quan P. Ly,et al. Gastric Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology. , 2022, Journal of the National Comprehensive Cancer Network : JNCCN.
[27] W. Long,et al. A Transfer Learning Radiomics Nomogram for Preoperative Prediction of Borrmann Type IV Gastric Cancer From Primary Gastric Lymphoma , 2022, Frontiers in Oncology.
[28] H. Bohnenberger,et al. A nomogram to predict the recurrence-free survival and analyze the utility of chemotherapy in stage IB non-small cell lung cancer , 2022, Translational lung cancer research.
[29] Zekuan Xu,et al. Quantification of Tumor Abnormal Proteins in the Diagnosis and Postoperative Prognostic Evaluation of Gastric Cancer , 2022, Clinical Medicine Insights. Oncology.
[30] C. Png,et al. Mucosal microbiome associates with progression to gastric cancer , 2022, Theranostics.
[31] Lei Gao,et al. A risk model based on autophagy-related lncRNAs for predicting prognosis and efficacy of immunotherapy and chemotherapy in gastric cancer patients , 2021, Aging.
[32] Dehua Yang,et al. Dietary Salt Intake and Gastric Cancer Risk: A Systematic Review and Meta-Analysis , 2021, Frontiers in Nutrition.
[33] M. Plummer,et al. The relative and attributable risks of cardia and non-cardia gastric cancer associated with Helicobacter pylori infection in China: a case-cohort study , 2021, The Lancet. Public health.
[34] Yilun Xu,et al. Integrative Radiogenomics Approach for Risk Assessment of Postoperative and Adjuvant Chemotherapy Benefits for Gastric Cancer Patients , 2021, Frontiers in Oncology.
[35] K. Matsuo,et al. Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, Helicobacter pylori Infection and Lifestyle-Related Risk Factors in a Japanese Population , 2021, Cancers.
[36] L. Dai,et al. Polygenic Risk Scores for Prediction of Gastric Cancer Based on Bioinformatics Screening and Validation of Functional lncRNA SNPs , 2021, Clinical and translational gastroenterology.
[37] Yi-Zi Zheng,et al. Prognostic Factors and a Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in situ with Microinvasion: A Population-Based Study , 2021, Clinical epidemiology.
[38] Hang Zheng,et al. Weighted Gene Co-expression Network Analysis Identifies a Cancer-Associated Fibroblast Signature for Predicting Prognosis and Therapeutic Responses in Gastric Cancer , 2021, Frontiers in Molecular Biosciences.
[39] Xiuying Wang,et al. 18F-FDG PET/CT Radiomics for Preoperative Prediction of Lymph Node Metastases and Nodal Staging in Gastric Cancer , 2021, Frontiers in Oncology.
[40] N. Hong,et al. CT‐detected extramural venous invasion‐related gene signature for the overall survival prediction in patients with gastric cancer , 2021, Cancer medicine.
[41] Y. Sheng,et al. Development and Validation of Nomograms to Predict Operative Link for Gastritis Assessment Any-Stage and Stages III–IV in the Chinese High-Risk Gastric Cancer Population , 2021, Frontiers in Medicine.
[42] P. Lambin,et al. A review in radiomics: Making personalized medicine a reality via routine imaging , 2021, Medicinal research reviews.
[43] Yingmu Cai,et al. Prognostic Model for Predicting Overall and Cancer-Specific Survival Among Patients With Cervical Squamous Cell Carcinoma: A SEER Based Study , 2021, Frontiers in Oncology.
[44] R. van Hillegersberg,et al. Risk Prediction Model of 90-Day Mortality After Esophagectomy for Cancer. , 2021, JAMA surgery.
[45] B. Tang,et al. Helicobacter pylori-Induced Heparanase Promotes H. pylori Colonization and Gastritis , 2021, Frontiers in Immunology.
[46] Xia Li,et al. Identification and Validation of Plasma Metabolomic Signatures in Precancerous Gastric Lesions That Progress to Cancer , 2021, JAMA network open.
[47] Ce Li,et al. Immune Landscape of Gastric Carcinoma Tumor Microenvironment Identifies a Peritoneal Relapse Relevant Immune Signature , 2021, Frontiers in Immunology.
[48] L. Xin,et al. Establishment of a prognostic model of four genes in gastric cancer based on multiple data sets , 2021, Cancer medicine.
[49] Wentao Liu,et al. Prediction Model of Tumor Regression Grade for Advanced Gastric Cancer After Preoperative Chemotherapy , 2021, Frontiers in Oncology.
[50] Yujie Zhang,et al. Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in elderly patients with gastric cancer after surgery. , 2021, Journal of gastrointestinal oncology.
[51] Chong Sun Hong,et al. Confusion plot for the confusion matrix , 2021 .
[52] F. Mégraud,et al. Gastric Cancer: Advances in Carcinogenesis Research and New Therapeutic Strategies , 2021, International journal of molecular sciences.
[53] Hongwei Li,et al. Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning , 2021, Nature Communications.
[54] A. Xu,et al. A model established using marital status and other factors from the Surveillance, Epidemiology, and End Results database for early stage gastric cancer , 2021, Journal of Investigative Medicine.
[55] Yongning Zhou,et al. A Novel Six-Gene-Based Prognostic Model Predicts Survival and Clinical Risk Score for Gastric Cancer , 2021, Frontiers in Genetics.
[56] M. Kanda,et al. Transcriptomic Profiling Identifies a Risk Stratification Signature for Predicting Peritoneal Recurrence and Micrometastasis in Gastric Cancer , 2021, Clinical Cancer Research.
[57] A. Jemal,et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries , 2021, CA: a cancer journal for clinicians.
[58] I. Choi,et al. Gastric Cancer Risk Prediction Using an Epidemiological Risk Assessment Model and Polygenic Risk Score , 2021, Cancers.
[59] Haibo Wang,et al. A predictive model for assessing prognostic risks in gastric cancer patients using gene expression and methylation data , 2021, BMC medical genomics.
[60] Yan Zhao,et al. CA724 predicts overall survival in locally advanced gastric cancer patients with neoadjuvant chemotherapy , 2021, BMC Cancer.
[61] Min Liu,et al. In silico development and validation of a novel glucose and lipid metabolism-related gene signature in gastric cancer , 2021, Translational cancer research.
[62] Chuan-feng Ke,et al. Prediction of distant metastasis and survival prediction of gastric cancer patients with metastasis to the liver, lung, bone, and brain: research based on the SEER database , 2021, Annals of translational medicine.
[63] Yanxia Sun,et al. Prognostic Model and Nomogram for Estimating Survival of Small Breast Cancer: A SEER-based Analysis. , 2020, Clinical breast cancer.
[64] M. Gu,et al. Identification of the subtypes of gastric cancer based on DNA methylation and the prediction of prognosis , 2020, Clinical epigenetics.
[65] Xiaobing Zhang,et al. [Application of deep learning in cancer prognosis prediction model]. , 2020, Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi.
[66] Tao Huang,et al. A Medical Decision Support System to Assess Risk Factors for Gastric Cancer Based on Fuzzy Cognitive Map , 2020, Comput. Math. Methods Medicine.
[67] Wanqing Chen,et al. Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model , 2020, Chinese journal of cancer research = Chung-kuo yen cheng yen chiu.
[68] E. Mayo-Wilson,et al. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews , 2020, BMJ.
[69] Yulan Wang,et al. Identification and prognostic value of metabolism-related genes in gastric cancer , 2020, Aging.
[70] F. Jiang,et al. Prognostic Prediction Using a Stemness Index-Related Signature in a Cohort of Gastric Cancer , 2020, Frontiers in Molecular Biosciences.
[71] F. Bai,et al. Prediction of gastric cancer risk: association between ZBTB20 genetic variance and gastric cancer risk in Chinese Han population , 2020, Bioscience reports.
[72] J. Toh,et al. Pathways of Gastric Carcinogenesis, Helicobacter pylori Virulence and Interactions with Antioxidant Systems, Vitamin C and Phytochemicals , 2020, International journal of molecular sciences.
[73] Menghong Sun,et al. Predictive model for risk of gastric cancer using genetic variants from genome‐wide association studies and high‐evidence meta‐analysis , 2020, Cancer medicine.
[74] Yuming Jiang,et al. Genomics Score Based on Genome-Wide Network Analysis for Prediction of Survival in Gastric Cancer: A Novel Prognostic Signature , 2020, Frontiers in Genetics.
[75] Xiao Fu,et al. Identification of a Tumor Microenvironment-relevant Gene set-based Prognostic Signature and Related Therapy Targets in Gastric Cancer , 2020, Theranostics.
[76] Yang Li,et al. Artificial intelligence in gastric cancer: a systematic review , 2020, Journal of Cancer Research and Clinical Oncology.
[77] D. Dong,et al. A Deep Learning Risk Prediction Model for Overall Survival in Patients with Gastric Cancer: A Multicenter Study. , 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[78] Mengyu Sun,et al. Prognostic Implications of Novel Gene Signatures in Gastric Cancer Microenvironment , 2020, Medical science monitor : international medical journal of experimental and clinical research.
[79] J. Machlowska,et al. Gastric Cancer: Epidemiology, Risk Factors, Classification, Genomic Characteristics and Treatment Strategies , 2020, International journal of molecular sciences.
[80] Jianhua Wu,et al. Development and validation of a hypoxia-immune-based microenvironment gene signature for risk stratification in gastric cancer , 2020, Journal of Translational Medicine.
[81] R. Safaralizadeh,et al. Helicobacter pylori‐related risk predictors of gastric cancer: The latest models, challenges, and future prospects , 2020, Cancer medicine.
[82] Zhenzhen Liu,et al. Pepsinogen Serology and Gastritis OLGA Staging in Mucosal Atrophy Assessment: A Cross-Sectional Study Involving East China Endoscopy Population , 2020, Gastroenterology research and practice.
[83] Edward L. Giovannucci,et al. Global Burden of 5 Major Types Of Gastrointestinal Cancer. , 2020, Gastroenterology.
[84] Xin-Zu Chen,et al. Prevalence of atrophic gastritis in southwest China and predictive strength of serum gastrin-17: A cross-sectional study (SIGES) , 2020, Scientific Reports.
[85] R. Sun,et al. Expression Status And Prognostic Value Of M6A-associated Genes in Gastric Cancer , 2020, Journal of Cancer.
[86] Haitao Zhao,et al. Development and Validation of a Prognostic Nomogram for Gastric Cancer Based on DNA Methylation-Driven Differentially Expressed Genes , 2020, International journal of biological sciences.
[87] L. Moradi,et al. Risk factors for stomach cancer: a systematic review and meta-analysis , 2020, Epidemiology and health.
[88] Yanfeng Hu,et al. A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine , 2019, BMC Genomics.
[89] Hao Wang,et al. Stromal-Immune Score-Based Gene Signature: A Prognosis Stratification Tool in Gastric Cancer , 2019, Front. Oncol..
[90] Yujie Zhang,et al. Development and validation of prognostic nomogram for young patients with gastric cancer. , 2019, Annals of translational medicine.
[91] Yoon Young Choi,et al. Individual Patient Data Meta-Analysis of the Value of Microsatellite Instability As a Biomarker in Gastric Cancer. , 2019, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[92] Zhongxue Chen,et al. Clinicopathological risk factors for gastric cancer: a retrospective cohort study in China , 2019, BMJ Open.
[93] T. Naito,et al. Prediction of future gastric cancer risk using a machine learning algorithm and comprehensive medical check-up data: A case-control study , 2019, Scientific Reports.
[94] Chaohui Yu,et al. Convolutional neural network for the diagnosis of early gastric cancer based on magnifying narrow band imaging , 2019, Gastric Cancer.
[95] Jie Tian,et al. The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges , 2019, Theranostics.
[96] A. Zwinderman,et al. SOURCE: A Registry-Based Prediction Model for Overall Survival in Patients with Metastatic Oesophageal or Gastric Cancer , 2019, Cancers.
[97] Prashanth Rawla,et al. Epidemiology of gastric cancer: global trends, risk factors and prevention , 2018, Przeglad gastroenterologiczny.
[98] Q. Gao,et al. Radiomics score: a potential prognostic imaging feature for postoperative survival of solitary HCC patients , 2018, BMC Cancer.
[99] Mohammed Ramdani,et al. Deep Learning: An Overview , 2018, SITA.
[100] Yonghong Zhang,et al. LASSO-based Cox-PH model identifies an 11-lncRNA signature for prognosis prediction in gastric cancer , 2018, Molecular medicine reports.
[101] Wenbing Lv,et al. Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancer , 2018, EBioMedicine.
[102] G. Rosman,et al. Artificial Intelligence in Surgery: Promises and Perils , 2018, Annals of surgery.
[103] B. Rapkin,et al. Can a gastric cancer risk survey identify high-risk patients for endoscopic screening? A pilot study. , 2018, The Journal of surgical research.
[104] Christa Boer,et al. Correlation Coefficients: Appropriate Use and Interpretation , 2018, Anesthesia and analgesia.
[105] T. Ninomiya,et al. Development and validation of a risk assessment tool for gastric cancer in a general Japanese population , 2018, Gastric Cancer.
[106] John Yuen Shyi Peng,et al. Automated Renal Cancer Grading Using Nuclear Pleomorphic Patterns. , 2018, JCO clinical cancer informatics.
[107] Jun-chi Yang,et al. Pathway- and clinical-factor-based risk model predicts the prognosis of patients with gastric cancer , 2018, Molecular medicine reports.
[108] Jun Xiao,et al. Prognostic significance of pretreatment serum carcinoembryonic antigen levels in gastric cancer with pathological lymph node-negative: A large sample single-center retrospective study , 2017, World journal of gastroenterology.
[109] Hongwei Zhang,et al. Diagnostic and prognostic value of CEA, CA19–9, AFP and CA125 for early gastric cancer , 2017, BMC Cancer.
[110] K. Koike,et al. Metaplasia in the Stomach—Precursor of Gastric Cancer? , 2017, International journal of molecular sciences.
[111] S. Ng,et al. Global Prevalence of Helicobacter pylori Infection: Systematic Review and Meta-Analysis. , 2017, Gastroenterology.
[112] J. Joo,et al. Alpha-fetoprotein is a significant prognostic factor for gastric cancer: Results from a propensity score matching analysis after curative resection. , 2017, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.
[113] J. Ajani,et al. Clinical Significance of Four Molecular Subtypes of Gastric Cancer Identified by The Cancer Genome Atlas Project , 2017, Clinical Cancer Research.
[114] Yulian Wu,et al. The potential value of serum pepsinogen for the diagnosis of atrophic gastritis among the health check-up populations in China: a diagnostic clinical research , 2017, BMC Gastroenterology.
[115] M. Camilleri,et al. Gastrointestinal Complications of Obesity. , 2017, Gastroenterology.
[116] M. Büchler,et al. Outcomes after extended pancreatectomy in patients with borderline resectable and locally advanced pancreatic cancer , 2016, The British journal of surgery.
[117] R. Malekzadeh,et al. Cigarette smoking and gastric cancer in the Stomach Cancer Pooling (StoP) Project , 2016, European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation.
[118] J. Lagergren,et al. A model for predicting individuals’ absolute risk of esophageal adenocarcinoma: Moving toward tailored screening and prevention , 2016, International journal of cancer.
[119] Ming-ming Nie,et al. Clinicopathologic characteristics and prognostic of gastric cancer in young patients , 2016, Scandinavian journal of gastroenterology.
[120] S. Nunobe,et al. Clinicopathological features of gastric cancer in young patients , 2016, Gastric Cancer.
[121] Tianqi Chen,et al. XGBoost: A Scalable Tree Boosting System , 2016, KDD.
[122] M. Inoue,et al. Prediction of the 10‐year probability of gastric cancer occurrence in the Japanese population: the JPHC study cohort II , 2016, International journal of cancer.
[123] David Smith,et al. Mass Spectrometric Analysis of Exhaled Breath for the Identification of Volatile Organic Compound Biomarkers in Esophageal and Gastric Adenocarcinoma , 2015, Annals of surgery.
[124] E. Oki,et al. Carbohydrate antigen 19-9 is a useful prognostic marker in esophagogastric junction adenocarcinoma , 2015, Cancer medicine.
[125] H. Sugihara,et al. Two distinct etiologies of gastric cardia adenocarcinoma: interactions among pH, Helicobacter pylori, and bile acids , 2015, Front. Microbiol..
[126] Jaw-Town Lin,et al. A tool to predict risk for gastric cancer in patients with peptic ulcer disease on the basis of a nationwide cohort. , 2015, Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association.
[127] R. Wong,et al. Ethnic Disparities in Gastric Cancer Incidence and Survival in the USA: An Updated Analysis of 1992–2009 SEER Data , 2014, Digestive Diseases and Sciences.
[128] Sharmila Anandasabapathy,et al. Gastric Cancer: Descriptive Epidemiology, Risk Factors, Screening, and Prevention , 2014, Cancer Epidemiology, Biomarkers & Prevention.
[129] H. Liang,et al. Characteristics and prognosis of gastric cancer in patients aged ≥ 70 years. , 2013, World journal of gastroenterology.
[130] Lu Leng,et al. PalmHash Code vs. PalmPhasor Code , 2013, Neurocomputing.
[131] H. Lang,et al. Endoscopic and surgical resection of T1a/T1b esophageal neoplasms: a systematic review. , 2013, World Journal of Gastroenterology.
[132] F. Cappuccio,et al. Habitual salt intake and risk of gastric cancer: a meta-analysis of prospective studies. , 2012, Clinical nutrition.
[133] J. Kitayama,et al. Clinical significance of CA125 and CA72-4 in gastric cancer with peritoneal dissemination , 2012, Gastric Cancer.
[134] C. la Vecchia,et al. A meta-analysis on alcohol drinking and esophageal and gastric cardia adenocarcinoma risk. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.
[135] A. Vickers. Prediction models: revolutionary in principle, but do they do more good than harm? , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[136] K. Miki. Gastric cancer screening by combined assay for serum anti-Helicobacter pylori IgG antibody and serum pepsinogen levels — “ABC method” , 2011, Proceedings of the Japan Academy. Series B, Physical and biological sciences.
[137] A. Kızıltunç,et al. Usefulness of serum pepsinogen levels as a screening test for atrophic gastritis and gastric cancer. , 2010, The Eurasian journal of medicine.
[138] C. Abnet,et al. The Gastric Cardia Is Not a Target for Human Papillomavirus–Induced Carcinogenesis , 2010, Cancer Epidemiology, Biomarkers & Prevention.
[139] S. Narod,et al. Family history and the risk of gastric cancer , 2009, British Journal of Cancer.
[140] C. Earle,et al. Treatment and outcomes of gastric cancer among United States‐born and foreign‐born Asians and Pacific Islanders , 2009, Cancer.
[141] David J Lee,et al. Cancer Incidence in First Generation U.S. Hispanics: Cubans, Mexicans, Puerto Ricans, and New Latinos , 2009, Cancer Epidemiology, Biomarkers & Prevention.
[142] M. Kubo,et al. Population-based prospective study of the combined influence of cigarette smoking and Helicobacter pylori infection on gastric cancer incidence: the Hisayama Study. , 2008, American journal of epidemiology.
[143] Chengwei Tang,et al. A rising trend of gastric cardia cancer in Gansu Province of China. , 2008, Cancer letters.
[144] C. Abnet,et al. A prospective study of tobacco, alcohol, and the risk of esophageal and gastric cancer subtypes. , 2007, American journal of epidemiology.
[145] Xiaocheng Wu,et al. Incidence of esophageal and gastric cancers among Hispanics, non-Hispanic whites and non-Hispanic blacks in the United States: subsite and histology differences , 2007, Cancer Causes & Control.
[146] S. Kikuchi,et al. Highly salted food and mountain herbs elevate the risk for stomach cancer death in a rural area of Japan , 2006, Journal of gastroenterology and hepatology.
[147] M. Blaser,et al. Opposing risks of gastric cardia and noncardia gastric adenocarcinomas associated with Helicobacter pylori seropositivity. , 2006, Journal of the National Cancer Institute.
[148] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[149] A. Neugut,et al. Epidemiology of gastric cancer. , 2006, World journal of gastroenterology.
[150] Pablo Tamayo,et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[151] S. Horvath,et al. Statistical Applications in Genetics and Molecular Biology , 2011 .
[152] Shoichiro Tsugane,et al. Salt, salted food intake, and risk of gastric cancer: Epidemiologic evidence , 2005, Cancer science.
[153] L. Bernstein,et al. Hiatal hernia, reflux symptoms, body size, and risk of esophageal and gastric adenocarcinoma , 2003, Cancer.
[154] M. Daly,et al. PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes , 2003, Nature Genetics.
[155] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[156] Jason H. Moore,et al. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions , 2003, Bioinform..
[157] W. Chow,et al. Risk of adenocarcinomas of the esophagus and gastric cardia in patients with gastroesophageal reflux diseases and after antireflux surgery. , 2001, Gastroenterology.
[158] L. Breiman. Random Forests , 2001, Encyclopedia of Machine Learning and Data Mining.
[159] J. H. Moore,et al. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. , 2001, American journal of human genetics.
[160] I A Basheer,et al. Artificial neural networks: fundamentals, computing, design, and application. , 2000, Journal of microbiological methods.
[161] L. Hansson,et al. Tobacco, alcohol and the risk of gastric cancer by sub‐site and histologic type , 1999, International journal of cancer.
[162] S. Schwartz,et al. The incidence of gastric carcinoma in Asian migrants to the United States and their descendants , 1999, Cancer Causes & Control.
[163] B. Wong,et al. Epidemiology of gastric cancer in relation to diet and Helicobacter pylori infection , 1998, Journal of gastroenterology and hepatology.
[164] Andrew P. Bradley,et al. The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..
[165] H. Adami,et al. Tobacco, alcohol and the risk of gastric cancer. A population‐based case‐control study in Sweden , 1994, International journal of cancer.
[166] P. Correa,et al. Phenotypic and genotypic events in gastric carcinogenesis. , 1994, Cancer research.
[167] E. Wynder,et al. Tobacco, alcohol intake, and diet in relation to adenocarcinoma of the esophagus and gastric cardia , 1993, Cancer Causes & Control.
[168] P. Correa,et al. Human gastric carcinogenesis: a multistep and multifactorial process--First American Cancer Society Award Lecture on Cancer Epidemiology and Prevention. , 1992, Cancer research.
[169] Y. Yang,et al. Construction and Evaluation of Gastric Cancer Risk Prediction Model , 2021, Indian Journal of Pharmaceutical Sciences.
[170] Kazuyoshi Yamamoto,et al. Validation of an assessment tool: Estimation of Postoperative Overall Survival for Gastric Cancer. , 2018, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.
[171] Ming Li,et al. Dual-source discrimination power analysis for multi-instance contactless palmprint recognition , 2015, Multimedia Tools and Applications.
[172] D. Chung,et al. Familial Gastric Cancers: A Review With Focus on Hereditary Diffuse Gastric Cancer Syndrome , 2014 .
[173] H. Shimada,et al. Clinical significance of serum tumor markers for gastric cancer: a systematic review of literature by the Task Force of the Japanese Gastric Cancer Association , 2013, Gastric Cancer.
[174] Shou-En Lu,et al. Cancer incidence among Korean-American immigrants in the United States and native Koreans in South Korea. , 2007, Cancer control : journal of the Moffitt Cancer Center.
[175] Vladimir Vapnik,et al. Support-vector networks , 2004, Machine Learning.
[176] G. Garrido Cantarero,et al. [The area under the ROC curve]. , 1996, Medicina clinica.
[177] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .