AIMC Topic: Helicobacter pylori
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Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy.
Scientific reports
Jul 1, 2025
Helicobacter pylori (HP) have chronically infected more than half of the world's population and is a cause of chronic gastritis, peptic ulcers and gastric carcinoma. The manual detection of HP in a glass slide with a microscope is extremely time-cons...
Retrospective cohort study of infection and risk stratification using 6-year UBT data.
Frontiers in public health
May 26, 2025
BACKGROUND: () infection is a major global health concern, linked to gastric cancer and metabolic disorders. Despite its widespread prevalence, accurate risk stratification remains challenging. This study aims to develop a machine learning (ML)-base...
Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.
Virulence
Mar 21, 2025
() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resistant strains is essential for the control of infection. In the present study, our goal is to leverage the whole-genome data of to develop practical an...
Multistage deep learning for classification of Helicobacter pylori infection status using endoscopic images.
Journal of gastroenterology
Jan 15, 2025
BACKGROUND: The automated classification of Helicobacter pylori infection status is gaining attention, distinguishing among uninfected (no history of H. pylori infection), current infection, and post-eradication. However, this classification has rela...
-targeted AI-driven vaccines: a paradigm shift in gastric cancer prevention.
Frontiers in immunology
Nov 28, 2024
, a globally prevalent pathogen Group I carcinogen, presents a formidable challenge in gastric cancer prevention due to its increasing antimicrobial resistance and strain diversity. This comprehensive review critically analyzes the limitations of con...
Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study.
BMC gastroenterology
Sep 30, 2024
BACKGROUND: The early diagnosis and treatment of Heliobacter pylori (H.pylori) gastrointestinal infection provide significant benefits to patients. We constructed a convolutional neural network (CNN) model based on an endoscopic system to diagnose H....
A deep learning-driven discovery of berberine derivatives as novel antibacterial against multidrug-resistant Helicobacter pylori.
Signal transduction and targeted therapy
Jul 8, 2024
Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high prevalence and resistance make it difficult to tackle. A graph neural network-based deep learning model, ...
Machine Learning-Based Prediction of Helicobacter pylori Infection Study in Adults.
Medical science monitor : international medical journal of experimental and clinical research
Jun 8, 2024
BACKGROUND Helicobacter pylori has a high infection rate worldwide, and epidemiological study of H. pylori is important. Artificial intelligence has been widely used in the field of medical research and has become a hotspot in recent years. This pape...
Machine Learning-Driven Classification of Urease Inhibitors Leveraging Physicochemical Properties as Effective Filter Criteria.
International journal of molecular sciences
Apr 13, 2024
Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic . Inhibiting urease activity offers a promising approach to combating infections and associated ailments, such as chronic kidney...
Classification of H. pylori Infection from Histopathological Images Using Deep Learning.
Journal of imaging informatics in medicine
Feb 8, 2024
Helicobacter pylori (H. pylori) is a widespread pathogenic bacterium, impacting over 4 billion individuals globally. It is primarily linked to gastric diseases, including gastritis, peptic ulcers, and cancer. The current histopathological method for ...
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