AIMC Topic: Intestinal Obstruction

Clear Filters Showing 11 to 17 of 17 articles

Development and validation of deep learning models for bowel obstruction on plain abdominal radiograph.

The Journal of international medical research
OBJECTIVE: Artificial intelligence (AI) could help medical practitioners in analyzing radiological images to determine the presence and site of bowel obstruction. This retrospective diagnostic study proposed a series of deep learning (DL) models for ...

Unveiling new patterns: A surgical deep learning model for intestinal obstruction management.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Swift and accurate decision-making is pivotal in managing intestinal obstructions. This study aims to integrate deep learning and surgical expertise to enhance decision-making in intestinal obstruction cases.

Automated Detection of Crohn's Disease Intestinal Strictures on Capsule Endoscopy Images Using Deep Neural Networks.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Passable intestinal strictures are frequently detected on capsule endoscopy [CE]. Such strictures are a major component of inflammatory scores. Deep neural network technology for CE is emerging. However, the ability of deep neura...

[Risk factors for postoperative intestinal obstruction in patients undergoing robot-assisted laparoscopic radical prostatectomy].

Zhonghua yi xue za zhi
To analyze the risk factors of postoperative intestinal obstruction (POI) in patients undergoing robot-assisted laparoscopic radical prostatectomy (RARP). The clinical data of 573 patients receiving RARP from January to December 2019 in Nanjing Dru...

[Prognosis of Patients after Palliative Stoma Creation].

Gan to kagaku ryoho. Cancer & chemotherapy
INTRODUCTION: We evaluated the effectiveness of palliative stomas created to resolve symptoms of bowel obstruction.

Detection of high-grade small bowel obstruction on conventional radiography with convolutional neural networks.

Abdominal radiology (New York)
The purpose of this pilot study is to determine whether a deep convolutional neural network can be trained with limited image data to detect high-grade small bowel obstruction patterns on supine abdominal radiographs. Grayscale images from 3663 clini...