Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Automatic segmentation of liver structures in multi-phase MRI using variants of nnU-Net and Swin UNETR.

Accurate segmentation of the liver parenchyma, portal veins, hepatic veins, and lesions from MRI is ...

Artificial oesophagus - a new technology for oesophageal surgery.

A new artificial oesophagus is described. The device allows minimally invasive oesophageal resection...

Non-invasive liver fibrosis screening on CT images using radiomics.

PURPOSE: To develop a radiomics machine learning model for detecting liver fibrosis on CT images of ...

F-FDG PET-based liver segmentation using deep-learning.

Organ segmentation using F-FDG PET images alone has not been extensively explored. Segmentation base...

Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.

Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the stan...

Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.

To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of...

Robust Polyp Detection and Diagnosis through Compositional Prompt-Guided Diffusion Models.

Colorectal cancer (CRC) is a significant global health concern, and early detection through screenin...

Early neoplastic lesions of the pancreas: initiation, progression, and opportunities for precancer interception.

Pancreatic ductal adenocarcinoma (PDAC) is known to progress from one of two main precursor lesions:...

Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.

OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic f...

Using machine learning algorithms to predict risk factors of heart failure after complete mesocolic excision in colorectal cancer patients.

Following complete mesocolic excision (CME), heart failure (HF) emerges as a significant complicatio...

Machine learning improves post-transplantation hepatocellular carcinoma recurrence prediction.

BACKGROUND: To enhance post-transplantation hepatocellular carcinoma (HCC) recurrence prediction by ...

Artificial Intelligence Enhances Diagnostic Accuracy of Contrast Enemas in Hirschsprung Disease Compared to Clinical Experts.

Contrast enema (CE) is widely used in the evaluation of suspected Hirschsprung disease (HD). Deep le...

Generative AI in hepatology: Transforming multimodal patient-generated data into actionable insights.

Cirrhosis care is inherently complex, marked by a high risk of acute decompensation and significant ...

Advances in nanorobotics for gastrointestinal surgery: a new frontier in precision medicine and minimally invasive therapeutics.

Nanorobotics is catalyzing a paradigm shift in GI surgery by synergizing nanoscale engineering, synt...

The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations.

Helicobacter pylori (H. pylori) is the most common carcinogenic pathogen globally and the leading ca...

Automated multiclass segmentation of liver vessel structures in CT images using deep learning approaches: a liver surgery pre-planning tool.

Accurate liver vessel segmentation is essential for effective liver surgery pre-planning, and reduci...

Identification of a 10-species microbial signature of inflammatory bowel disease by machine learning and external validation.

Genetic and microbial factors influence inflammatory bowel disease (IBD), prompting our study on non...

Pathological omics prediction of early and advanced colon cancer based on artificial intelligence model.

Artificial intelligence (AI) models based on pathological slides have great potential to assist path...

Colon cancer survival prediction from gland shapes within histology slides using deep learning.

This study investigates the application of deep learning techniques for segmenting glands in histopa...

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