Latest AI and machine learning research in gastroenterology for healthcare professionals.
Dipeptidyl peptidase-IV (DPP-IV) is a circulating blood biomarker that diagnose pancreatic and thyroid cancers, as well as type 2 diabetes. Although current DPP-IV detection methods show promise, real-time detection in whole blood is limited, as blood samples require tedious pre-treatment. To overcome these limitations, a DPP-IV targeted electrochemical substrate, DPPLPOH (DiPeptidyl Peptidase Lat...
Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a common complication in patients undergoing ERCP for choledocholithiasis, yet effective predictive models are lacking. This study included 2,247 patients who underwent ERCP for complete stone removal at the First Affiliated Hospital of USTC from January 2015 to January 2023. Six machine learning algorithms were utili...
INTRODUCTION: Artificial intelligence (AI) has rapidly advanced and shows great potential in the prediction, diagnosis, treatment, and prognosis of fa...
BACKGROUND: To develop a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CECT) to assess the rat sarcoma (RAS) onc...
The gastrointestinal (GI) system is fundamental to human health, supporting digestion, nutrient absorption, and waste elimination. Disruptions in GI f...
Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practice in radiopharmaceutical therapy (RPT) compared wi...
Caffeine, a widely consumed stimulant, is known for its rapid absorption and clearance, leading to fluctuations in plasma concentration and potential ...
INTRODUCTION: Measurement of gastrointestinal (GI) transit is increasingly becoming a valuable tool in understanding the pathophysiology of symptoms o...
Organoid technology, as an emerging field within biotechnology, has demonstrated transformative potential in advancing precision medicine. This review...
This study evaluated the effects of a commercial probiotic containing and on the growth performance, intestinal histological structure, body composi...
OBJECTIVE: Endoscopy is a convenient and widely used method to evaluate adenoid size, but the subjectivity of its image diagnosis can result in over- ...
BACKGROUND: Large language models like ChatGPT have demonstrated potential in medical image interpretation, but their efficacy in liver histopathologi...
This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic ...
BACKGROUND: Advancements in the management of gastric cancer (GC) and innovative therapeutic approaches highlight the significance of the role of biom...
BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complica...
PURPOSE: Automated localization of critical anatomical structures in endoscopic pituitary surgery is crucial for enhancing patient safety and surgical...
BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This stu...
BACKGROUND AND AIM: Artificial intelligence (AI) networks offer significant potential for predicting immunotherapy outcomes in gastrointestinal cancer...
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the...
Inflammatory bowel disease (IBD) is increasing globally, with risk factors still poorly understood and influenced by both genetic and environmental fa...