AI Medical Compendium Journal:
Digestive diseases and sciences

Showing 1 to 10 of 21 articles

Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.

Digestive diseases and sciences
BACKGROUND: Major society guidelines recommend transarterial chemoembolization (TACE) as the standard of care for intermediate-stage hepatocellular carcinoma (HCC) patients. However, predicting treatment response remains challenging.

Predicting Portal Pressure Gradient in Patients with Decompensated Cirrhosis: A Non-invasive Deep Learning Model.

Digestive diseases and sciences
BACKGROUND: A high portal pressure gradient (PPG) is associated with an increased risk of failure to control esophagogastric variceal hemorrhage and refractory ascites in patients with decompensated cirrhosis. However, direct measurement of PPG is in...

Association Between Body Composition Measured by Artificial Intelligence and Long-Term Sequelae After Acute Pancreatitis.

Digestive diseases and sciences
BACKGROUND/OBJECTIVES: The clinical utility of body composition in the development of complications of acute pancreatitis (AP) remains unclear. We aimed to describe the associations between body composition and the recurrence of AP.

Ethical Implications of Artificial Intelligence in Gastroenterology: The Co-pilot or the Captain?

Digestive diseases and sciences
Though artificial intelligence (AI) is being widely implemented in gastroenterology (GI) and hepatology and has the potential to be paradigm shifting for clinical practice, its pitfalls must be considered along with its advantages. Currently, althoug...

Validation of a Machine Learning Algorithm, EVendo, for Predicting Esophageal Varices in Hepatocellular Carcinoma.

Digestive diseases and sciences
BACKGROUND: Treatment with atezolizumab and bevacizumab has become standard of care for advanced unresectable hepatocellular carcinoma (HCC) but carries an increased gastrointestinal bleeding risk. Therefore, patients are often required to undergo es...

Video-Based Deep Learning to Detect Dyssynergic Defecation with 3D High-Definition Anorectal Manometry.

Digestive diseases and sciences
BACKGROUND: We developed a deep learning algorithm to evaluate defecatory patterns to identify dyssynergic defecation using 3-dimensional high definition anal manometry (3D-HDAM).

Computed Tomography-Based Deep Learning Nomogram Can Accurately Predict Lymph Node Metastasis in Gastric Cancer.

Digestive diseases and sciences
BACKGROUND: Computed tomography is the most commonly used imaging modality for preoperative assessment of lymph node status, but the reported accuracy is unsatisfactory.

Artificial Intelligence for Inflammatory Bowel Diseases (IBD); Accurately Predicting Adverse Outcomes Using Machine Learning.

Digestive diseases and sciences
BACKGROUND: Inflammatory Bowel Diseases with its complexity and heterogeneity could benefit from the increased application of Artificial Intelligence in clinical management.

Use of Artificial Intelligence in the Prediction of Malignant Potential of Gastric Gastrointestinal Stromal Tumors.

Digestive diseases and sciences
BACKGROUND AND AIMS: This study aimed to investigate whether AI via a deep learning algorithm using endoscopic ultrasonography (EUS) images could predict the malignant potential of gastric gastrointestinal stromal tumors (GISTs).