Gastroenterology

Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imaging

Colorectal polyps are generally benign alterations that, if not identified promptly and managed successfully, can progress to cancer and cause affectations on the colon mucosa, known as adenocarcinoma. Today advances in Deep Learning have demonstrated the ability to achieve significant performance in image classification and detection in medical diagnosis applications. Nevertheless, these models...

Design, Fabrication, and Characterization of a User-Friendly Microfluidic Device for Studying Liver Zonation-on-Chip (ZoC)

Liver zonation is a fundamental characteristic of hepatocyte spatial heterogeneity, which is challenging to recapitulate in traditional cell cultures. This study presents a novel microfluidic device designed to induce zonation in liver cell cultures by establishing an oxygen gradient using standard laboratory gases. The device consists of two layers; a bottom layer containing a gas channel netwo...

Machine Learning Identifies Metabolic Dysfunction-Associated Steatotic Liver Disease in Patients With Diabetes Mellitus.

CONTEXT: The presence of metabolic dysfunction-associated steatotic liver disease (MASLD) in patients with diabetes mellitus (DM) is associated with a...

A 3D Pancreatic Cancer Model with Integrated Optical Sensors for Noninvasive Metabolism Monitoring and Drug Screening

A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heter...

Computed tomography-based radiomics combined with machine learning allows differentiation between primary intestinal lymphoma and Crohn's disease.

BACKGROUND: Due to similar clinical manifestations and imaging signs, differential diagnosis of primary intestinal lymphoma (PIL) and Crohn's disease ...

Metagenomic analysis reveals shared and distinguishing features in horse and donkey gut microbiome and maternal resemblance of the microbiota in hybrid equids

Mammalian gut microbiomes are essential for host functions like digestion, immunity, and nutrient utilization. This study examines the gut microbiom...

Risk factors and development of machine learning diagnostic models for lateral lymph node metastasis in rectal cancer: multicentre study.

BACKGROUND: The diagnostic criteria for lateral lymph node metastasis in rectal cancer have not been established. This research aimed to investigate t...

Robot-assisted distal gastrectomy and local resection for gastric cancer and gastrointestinal stromal tumor.

Gastrointestinal stromal tumors surrounding the esophagogastric junction are often challenging to resect, with no consensus regarding the optimal surg...

A case of robot-assisted resection for cecum cancer with anomalous venous confluence.

There are many reports on the positional relationship between the ileocolic artery and superior mesenteric vein (SMV). However, there have been no rep...

A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma.

PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocell...

Using Machine Learning and miRNA for the Diagnosis of Esophageal Cancer.

BACKGROUND: Esophageal cancer (EC) remains a global health challenge, often diagnosed at advanced stages, leading to high mortality rates. Current dia...

Predictive value of circulating lymphocyte subsets and inflammatory indexes for neoadjuvant chemoradiotherapy response in rectal mucinous adenocarcinoma patients: A machine learning approach.

INTRODUCTION: In this study, we aimed to evaluate the predictive value of circulating lymphocyte subsets and inflammatory indexes in response to neoad...

Multi-dataset Collaborative Learning for Liver Tumor Segmentation.

Automatic segmentation of biomedical images has emerged due to its potential in improving real-world clinical processes and has achieved great success...

Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques.

Pancreatitis is a major public health issue world-wide; studies show an increase in the number of people experiencing pancreatitis. Identifying peri-p...

Multi-task Learning Graph Neural Networks for Cancer Prognosis Prediction with Genomic Data.

Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a n...

Deep STI: Deep Stochastic Time-series Imputation on Electronic Health Records.

Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich datasets for various disease analyses through advance...

Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.

Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucial in gastrointestinal (GI) cancer prognosis and tr...

Towards Non-Invasive Swallowing Assessment: an AI-Powered Interface for Swallowing Kinematic Analysis using High-Resolution Cervical Auscultation.

Swallowing is a pivotal physiological function for human sustenance and hydration. Dysfunctions, termed dysphagia, necessitate prompt and precise diag...

Grade classification of nasal obstruction from endoscopy videos using machine learning.

Nasal obstruction (NO), referring to blockage in the nasal cavity, is prevalent, affecting approximately one-third of the adult population. Consequent...

Improving Endoscopy Lesion Classification Using Self-Supervised Deep Learning.

In this work, we assess the impact of self-supervised learning (SSL) approaches on the detection of gastritis atrophy (GA) and intestinal metaplasia (...