AIMC Topic: Intestine, Small

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Mechanics of small intestine motility for oral macromolecular delivery: modelling segmentation versus peristalsis.

Drug delivery
Intestinal motility, including peristalsis and segmentation, drives complex fluid movements critical for the oral delivery of biologics and other macromolecules. Despite advances, oral delivery remains commercially limited by low bioavailability, oft...

Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning.

BMC gastroenterology
BACKGROUND: Small intestinal neuroendocrine neoplasms (SI-NENs), a subgroup of neuroendocrine tumors originating from neuroendocrine cells in the small intestine, present significant therapeutic challenges, and their relationship with ferroptosis-a r...

Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.

Journal of gastroenterology and hepatology
BACKGROUND: Capsule endoscopy (CE) is a valuable tool used in the diagnosis of small intestinal lesions. The study aims to systematically review the literature and provide a meta-analysis of the diagnostic accuracy, specificity, sensitivity, and nega...

Use of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.

Journal of clinical gastroenterology
Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neural Networks, are increasingly being used for detecting and managing gastrointestinal conditions. Recent advancements involve using Artificial Neural ...

The Use of Artificial Intelligence for Endoscopic Evaluation of the Small Bowel.

Gastrointestinal endoscopy clinics of North America
There remains great potential for widespread implementation of artificial intelligence (AI) in managing small bowel disorders. Studies have shown excellent accuracy in diagnosing various diseases and lesions throughout the small bowel, with most show...

Toward automated small bowel capsule endoscopy reporting using a summarizing machine learning algorithm: The SUM UP study.

Clinics and research in hepatology and gastroenterology
BACKGROUND AND OBJECTIVES: Deep learning (DL) algorithms demonstrate excellent diagnostic performance for the detection of vascular lesions via small bowel (SB) capsule endoscopy (CE), including vascular abnormalities with high (P2), intermediate (P1...

Establishing an AI model and application for automated capsule endoscopy recognition based on convolutional neural networks (with video).

BMC gastroenterology
BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, the need to process a vast number of images imposes a significant workload on physicians, leading to a high risk of missed diagnoses. This study aims t...

Artificial intelligence-based quantification of lymphocytes in feline small intestinal biopsies.

Veterinary pathology
Feline chronic enteropathy is a poorly defined condition of older cats that encompasses chronic enteritis to low-grade intestinal lymphoma. The histological evaluation of lymphocyte numbers and distribution in small intestinal biopsies is crucial for...

AI-KODA score application for cleanliness assessment in video capsule endoscopy frames.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
BACKGROUND: Currently, there is no automated method for assessing cleanliness in video capsule endoscopy (VCE). Our objectives were to automate the process of evaluating and collecting medical scores of VCE frames according to the existing KOrea-Cana...