Background: Endoscopic Ultrasound (EUS) is widely used for the diagnosis of bilio-pancreatic and gastrointestinal (GI) tract diseases, for the evaluation of subepithelial lesions, and for sampling of lymph nodes and solid masses located next to the GI tract. The role of Artificial Intelligence in healthcare in growing. This review aimed to provide an overview of the current state of AI in EUS from imaging to pathological diagnosis and training. Methods: AI algorithms can assist in lesion detection and characterization in EUS by analyzing EUS images and identifying suspicious areas that may require further clinical evaluation or biopsy sampling. Deep learning techniques, such as convolutional neural networks (CNNs), have shown great potential for tumor identification and subepithelial lesion (SEL) evaluation by extracting important features from EUS images and using them to classify or segment the images. Results: AI models with new features can increase the accuracy of diagnoses, provide faster diagnoses, identify subtle differences in disease presentation that may be missed by human eyes, and provide more information and insights into disease pathology. Conclusions: The integration of AI in EUS images and biopsies has the potential to improve the diagnostic accuracy, leading to better patient outcomes and to a reduction in repeated procedures in case of non-diagnostic biopsies.

Crohn’s disease (CD) is a chronic inflammatory gastrointestinal disorder requiring lifelong medications. The currently approved drugs for CD are associated with relevant side effects and several studies suggest an increased use of nutraceuticals among CD patients, seeking for what is perceived as a more “natural” approach in controlling this highly morbid condition. Nutraceuticals are foods or foods’ components with beneficial health properties that could aid in CD treatment for their anti-inflammatory, analgesic and immunoregulatory activities that come along with safety, high tolerability, easy availability and affordability. Depending on their biological effect, nutraceuticals’ support could be employed in different subsets of CD patients, both those with active disease, as adjunctive immunomodulatory therapies, and/or in quiescent disease to provide symptomatic relief in patients with residual functional symptoms. Despite the increasing interest of the general public, both limited research and lack of education from healthcare professionals regarding their real clinical effectiveness account for the increasing number of patients turning to unconventional sources. Professionals should recognize their widespread use and the evidence base for or against their efficacy to properly counsel IBD patients. Overall, nutraceuticals appear to be safe complements to conventional therapies; nonetheless, little quality evidence supports a positive impact on underlying inflammatory activity.

Background: Endoscopic Ultrasound (EUS) is widely used for the diagnosis of bilio-pancreatic and gastrointestinal (GI) tract diseases, for the evaluation of subepithelial lesions, and for sampling of lymph nodes and solid masses lo-cated next to the GI tract. The role of Artificial Intelligence in healthcare in growing. This review aimed to provide an overview of the current state of AI in EUS from imaging to pathological diagnosis and training. Methods: AI algorithms can assist in lesion detection and characterization in EUS by analysing EUS images and identifying suspicious areas that may require further clinical evaluation or biopsy sampling. Deep learning tech-niques, such as convolutional neural networks (CNNs), have shown great potential for tumour identification and subepithelial lesion (SEL) evaluation by extracting important features from EUS images and using them to classify or segment the images. Results: AI models with new features can increase the accuracy of diagnoses, provide faster diagnoses, identify subtle differences in disease presentation that may be missed by human eyes, and provide more information and in-sights into disease pathology. Conclusions: The integration of AI in EUS images and biopsies has the potential to improve the diagnostic accura-cy, leading to better patient outcomes and to a reduction of repeated procedures in case of non-diagnostic biopsies.