Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21983, first published .
Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Artificial Intelligence for the Prediction of Helicobacter Pylori Infection in Endoscopic Images: Systematic Review and Meta-Analysis Of Diagnostic Test Accuracy

Journals

  1. Tanabe S. Cancer recognition of artificial intelligence. WArtificial Intelligence in Cancer 2021;2(1):1 View
  2. Bang C, Lim H, Jeong H, Hwang S. Use of Endoscopic Images in the Prediction of Submucosal Invasion of Gastric Neoplasms: Automated Deep Learning Model Development and Usability Study. Journal of Medical Internet Research 2021;23(4):e25167 View
  3. Yang H, Hu B. Application of artificial intelligence to endoscopy on common gastrointestinal benign diseases. Artificial Intelligence in Gastrointestinal Endoscopy 2021;2(2):25 View
  4. Dore M, Pes G. What Is New in Helicobacter pylori Diagnosis. An Overview. Journal of Clinical Medicine 2021;10(10):2091 View
  5. Yang H, Hu B. Diagnosis of Helicobacter pylori Infection and Recent Advances. Diagnostics 2021;11(8):1305 View
  6. Bordin D, Voynovan I, Andreev D, Maev I. Current Helicobacter pylori Diagnostics. Diagnostics 2021;11(8):1458 View
  7. Visaggi P, de Bortoli N, Barberio B, Savarino V, Oleas R, Rosi E, Marchi S, Ribolsi M, Savarino E. Artificial Intelligence in the Diagnosis of Upper Gastrointestinal Diseases. Journal of Clinical Gastroenterology 2022;56(1):23 View
  8. Dilaghi E, Lahner E, Annibale B, Esposito G. Systematic review and meta-analysis: Artificial intelligence for the diagnosis of gastric precancerous lesions and Helicobacter pylori infection. Digestive and Liver Disease 2022;54(12):1630 View
  9. Tao Y, Hu H, Li J, Li M, Zheng Q, Zhang G, Ni M. A preliminary study on the application of deep learning methods based on convolutional network to the pathological diagnosis of PJI. Arthroplasty 2022;4(1) View
  10. Luo Q, Yang H, Hu B. Application of artificial intelligence in the endoscopic diagnosis of early gastric cancer, atrophic gastritis, and Helicobacter pylori infection. Journal of Digestive Diseases 2022;23(12):666 View
  11. Khanzadeh S, Tahernia H, Hernandez J, Sarcone C, Lucke-Wold B, Salimi A, Tabatabaei F, Xu G. Predictive Role of Neutrophil to Lymphocyte Ratio in Adnexal Torsion: A Systematic Review and Meta-Analysis. Mediators of Inflammation 2022;2022:1 View
  12. Bhattamisra S, Banerjee P, Gupta P, Mayuren J, Patra S, Candasamy M. Artificial Intelligence in Pharmaceutical and Healthcare Research. Big Data and Cognitive Computing 2023;7(1):10 View
  13. Quach D, Aoki R, Iga A, Le Q, Kawamura T, Yamashita K, Tanaka S, Yoshihara M, Hiyama T. Diagnostic Accuracy of H. pylori Status by Conventional Endoscopy: Time-Trend Change After Eradication and Impact of Endoscopic Image Quality. Frontiers in Medicine 2022;8 View
  14. Zhang P, Xiao Y, Sun X, Lin X, Koo S, Yaremenko A, Qin D, Kong N, Farokhzad O, Tao W. Cancer nanomedicine toward clinical translation: Obstacles, opportunities, and future prospects. Med 2023;4(3):147 View
  15. Buendgens L, Cifci D, Ghaffari Laleh N, van Treeck M, Koenen M, Zimmermann H, Herbold T, Lux T, Hann A, Trautwein C, Kather J. Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy. Scientific Reports 2022;12(1) View
  16. Yuan X, Guo L, Liu W, Zeng X, Mou Y, Bai S, Pan Z, Zhang T, Pu W, Wen C, Wang J, Zhou Z, Feng J, Hu B. Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study. Journal of Gastroenterology and Hepatology 2022;37(1):169 View
  17. Kim H, Gong E, Bang C, Lee J, Suk K, Baik G. Computer-Aided Diagnosis of Gastrointestinal Protruded Lesions Using Wireless Capsule Endoscopy: A Systematic Review and Diagnostic Test Accuracy Meta-Analysis. Journal of Personalized Medicine 2022;12(4):644 View
  18. Wong M, Rogers B, Liu M, Lei W, Liu T, Yi C, Hung J, Liang S, Tseng C, Wang J, Wu P, Chen C. Application of Artificial Intelligence in Measuring Novel pH-Impedance Metrics for Optimal Diagnosis of GERD. Diagnostics 2023;13(5):960 View
  19. El-Nakeep S, El-Nakeep M. Artificial intelligence for cancer detection in upper gastrointestinal endoscopy, current status, and future aspirations. Artificial Intelligence in Gastroenterology 2021;2(5):124 View
  20. Sousa C, Ferreira R, Santos S, Azevedo N, Melo L. Advances on diagnosis of Helicobacter pylori infections. Critical Reviews in Microbiology 2023;49(6):671 View
  21. Yang H, Hu B. Early gastrointestinal cancer: The application of artificial intelligence. Artificial Intelligence in Gastrointestinal Endoscopy 2021;2(4):185 View
  22. Yoo B, Houston K, D'Souza S, Elmahdi A, Davis I, Vilela A, Parekh P, Johnson D. Advances and horizons for artificial intelligence of endoscopic screening and surveillance of gastric and esophageal disease. Artificial Intelligence in Medical Imaging 2022;3(3):70 View
  23. Zhao Y, Hu B, Wang Y, Yin X, Jiang Y, Zhu X. Identification of gastric cancer with convolutional neural networks: a systematic review. Multimedia Tools and Applications 2022;81(8):11717 View
  24. Chen P, Lu Y, Kang Y, Chang C. The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study. Journal of Medical Internet Research 2022;24(5):e27694 View
  25. Bang C. Artificial Intelligence in the Analysis of Upper Gastrointestinal Disorders. The Korean Journal of Helicobacter and Upper Gastrointestinal Research 2021;21(4):300 View
  26. Kusano Y, Funada K, Yamaguchi M, Sugawara M, Tamano M. Dietary counseling based on artificial intelligence for patients with nonalcoholic fatty liver disease. Artificial Intelligence in Gastroenterology 2022;3(4):105 View
  27. Wu S, Wang J, Guo Q, Lan H, Zhang J, Wang L, Janne E, Luo X, Wang Q, Song Y, Mathew J, Xun Y, Yang N, Lee M, Chen Y. Application of artificial intelligence in clinical diagnosis and treatment: an overview of systematic reviews. Intelligent Medicine 2022;2(2):88 View
  28. Bang C, Lee J, Baik G. Computer-Aided Diagnosis of Gastrointestinal Ulcer and Hemorrhage Using Wireless Capsule Endoscopy: Systematic Review and Diagnostic Test Accuracy Meta-analysis. Journal of Medical Internet Research 2021;23(12):e33267 View
  29. Bang C, Lee J, Baik G. Computer-Aided Diagnosis of Diminutive Colorectal Polyps in Endoscopic Images: Systematic Review and Meta-analysis of Diagnostic Test Accuracy. Journal of Medical Internet Research 2021;23(8):e29682 View
  30. Pecere S, Milluzzo S, Esposito G, Dilaghi E, Telese A, Eusebi L. Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases. Diagnostics 2021;11(9):1575 View
  31. Goyal H, Sherazi S, Mann R, Gandhi Z, Perisetti A, Aziz M, Chandan S, Kopel J, Tharian B, Sharma N, Thosani N. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers 2021;13(21):5494 View
  32. Yacob Y, Alquran H, Mustafa W, Alsalatie M, Sakim H, Lola M. H. pylori Related Atrophic Gastritis Detection Using Enhanced Convolution Neural Network (CNN) Learner. Diagnostics 2023;13(3):336 View
  33. Klein S, Duda D. Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas. Cancers 2021;13(19):4919 View
  34. Kang S. Endoscopic Scoring System for Predicting Helicobacter pylori Infection. The Korean Journal of Helicobacter and Upper Gastrointestinal Research 2022;22(4):253 View
  35. Wang Y, Hong Y, Wang Y, Zhou X, Gao X, Yu C, Lin J, Liu L, Gao J, Yin M, Xu G, Liu X, Zhu J. Automated Multimodal Machine Learning for Esophageal Variceal Bleeding Prediction Based on Endoscopy and Structured Data. Journal of Digital Imaging 2022;36(1):326 View
  36. Mărginean C, Meliț L, Săsăran M. Traditional and Modern Diagnostic Approaches in Diagnosing Pediatric Helicobacter pylori Infection. Children 2022;9(7):994 View
  37. Brenner A, Laoveeravat P, Carey P, Joiner D, Mardini S, Jovani M. Artificial intelligence using advanced imaging techniques and cholangiocarcinoma: Recent advances and future direction. Artificial Intelligence in Gastroenterology 2022;3(3):88 View
  38. Seo J, Hong H, Ryu W, Kim D, Chun J, Kwak M. Development and validation of a convolutional neural network model for diagnosing Helicobacter pylori infections with endoscopic images: a multicenter study. Gastrointestinal Endoscopy 2023;97(5):880 View
  39. Gong E, Bang C, Lee J, Baik G, Lim H, Jeong J, Choi S, Cho J, Kim D, Lee K, Shin S, Sigmund D, Moon B, Park S, Lee S, Bang K, Son D. Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study. Endoscopy 2023;55(08):701 View
  40. Popovic D, Glisic T, Milosavljevic T, Panic N, Marjanovic-Haljilji M, Mijac D, Stojkovic Lalosevic M, Nestorov J, Dragasevic S, Savic P, Filipovic B. The Importance of Artificial Intelligence in Upper Gastrointestinal Endoscopy. Diagnostics 2023;13(18):2862 View
  41. Kiran N, Sapna F, Kiran F, Kumar D, Raja F, Shiwlani S, Paladini A, Sonam F, Bendari A, Perkash R, Anjali F, Varrassi G. Digital Pathology: Transforming Diagnosis in the Digital Age. Cureus 2023 View
  42. Lee S. Role of linked color imaging for upper gastrointestinal disease: present and future. Clinical Endoscopy 2023;56(5):546 View
  43. Buzás G. Helicobacter pylori – 2021. Orvosi Hetilap 2021;162(32):1275 View
  44. . Guidelines for diagnosis and treatment of chronic gastritis inChina(2022,Shanghai). Journal of Digestive Diseases 2023;24(3):150 View
  45. Kang D, Lee K, Kim J. Diagnostic usefulness of deep learning methods for Helicobacter pylori infection using esophagogastroduodenoscopy images. JGH Open 2023;7(12):875 View
  46. An P, Wang Z. Application value of an artificial intelligence-based diagnosis and recognition system in gastroscopy training for graduate students in gastroenterology: a preliminary study. Wiener Medizinische Wochenschrift 2024;174(9-10):173 View
  47. Wu R, Qin K, Fang Y, Xu Y, Zhang H, Li W, Luo X, Han Z, Liu S, Li Q. Application of the convolution neural network in determining the depth of invasion of gastrointestinal cancer: a systematic review and meta-analysis. Journal of Gastrointestinal Surgery 2024;28(4):538 View
  48. Gong E, Bang C, Lee J. Computer‐aided diagnosis in real‐time endoscopy for all stages of gastric carcinogenesis: Development and validation study. United European Gastroenterology Journal 2024;12(4):487 View
  49. Xu J, Deng M, Tang X. Comments on "Global Prevalence of Helicobacter pylori Infection and Incidence of Gastric Cancer Between 1980 and 2022". Gastroenterology 2024;167(4):817 View
  50. Lara Icaza J, Tapia R, Triana C, Ramírez L. Refractoriness to anti‐Helicobacter pylori treatment attributed to phenotypic resistance patterns in patients with gastroduodenopathy in Guayaquil‐Ecuador. Helicobacter 2024;29(2) View
  51. Lee J, Yoo I, Yeniova A, Lee S. The Diagnostic Performance of Linked Color Imaging Compared to White Light Imaging in Endoscopic Diagnosis of Helicobacter pylori Infection: A Systematic Review and Meta-Analysis. Gut and Liver 2024;18(3):444 View
  52. Swied M, Alom M, Daaboul O, Swied A. Screening and Diagnostic Advances of Artificial Intelligence in Endoscopy. Innovations in Digital Health, Diagnostics, and Biomarkers 2024;4(2024):31 View
  53. Zha B, Cai A, Wang G. Diagnostic Accuracy of Artificial Intelligence in Endoscopy: Umbrella Review. JMIR Medical Informatics 2024;12:e56361 View
  54. Hao W, Huang L, Li X, Jia H. Novel endoscopic techniques for the diagnosis of gastric Helicobacter pylori infection: a systematic review and network meta-analysis. Frontiers in Microbiology 2024;15 View
  55. Qasem S. Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of Helicobacter pylori Infection. Computers 2024;13(9):217 View
  56. Abdullah Jan S, Sayed Zekria H. Endoscopic appearances of gastric mucosa in different endoscopic models according to H. pylori infection status. JGH Open 2024;8(9) View
  57. Zou P, Zhu J, Zhao Z, Mei H, Zhao J, Sun W, Wang G, Chen D, Fan L, Lan C. Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study. BMC Gastroenterology 2024;24(1) View
  58. Huang H, Li Y, Wu Y, Zhao X, Gao H, Xie X, Wu L, Zhao H, Li L, Zhang J, Chen M, Wu Q. Advances in Helicobacter pylori detection technology: From pathology-based to multi-omic based methods. TrAC Trends in Analytical Chemistry 2025;182:118041 View

Books/Policy Documents

  1. Ashrafuzzaman M, Mahmudul Haque Milu M, Anjum A, Khanam F, Asadur Rahman M. Big Data Analytics for Healthcare. View
  2. Sood N, Chirayath S, Bahirwani J, Patel H, Kim E, Reddy-Patel N, Lin H, Martins N. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 2. View