Gastroenterology

A High-Quality Endoscopic Image Dataset with Annotated Recurrent Laryngeal Nerve for AI-Assisted Thyroid Surgery.

The integration of artificial intelligence (AI) into surgical navigation represents a pivotal advancement in modern operative medicine. In endoscopic thyroidectomy, safeguarding the recurrent laryngeal nerve (RLN) is of critical importance due to its vulnerability to iatrogenic injury, which affects 3-8% of cases and can lead to serious complications such as vocal cord paralysis. However, existing...

Intestinal microbiome and acute transplanted kidney rejection - results of a single-center, case-control study.

Machine learning in the prediction of liver iron concentration and iron chelation therapy adjustment.

OBJECTIVES: Iron chelation therapy titration is managed by hematologists who monitor iron levels and adjust medication dosages to achieve patient outc...

Prospectively screening for venous thromboembolism in patients with esophagectomy for cancer improves survival: The complexity of simplicity.

BACKGROUND: We implemented a prospective screening program to detect deep venous thromboembolism and define its prevalence in patients with esophageal...

An algorithm-enhanced stool DNA system improves the differential diagnosis of colorectal cancer versus Crohn's disease in high-risk symptomatic patients.

BACKGROUND AND OBJECTIVE: Crohn's disease (CD) and colorectal cancer (CRC) share many clinical symptoms, making non-invasive differential diagnosis di...

Construction of an interpretable multimodal image model for differentiating T1-stage nasopharyngeal carcinoma from benign hyperplasia.

BACKGROUND AND OBJECTIVE: Differentiating T1-stage nasopharyngeal carcinoma (NPC) from benign hyperplasia (BH) is challenging. This study aims to cons...

Computer-assisted adenoma detection colonoscopy with an ENDO-AID artificial intelligence system and Endocuff- versus Endocuff-assisted colonoscopy: a randomized controlled trial.

BACKGROUND: Compared with conventional colonoscopy, computer-assisted adenoma detection (CADe) colonoscopy and Endocuff-Vision (EV) have been shown to...

Gut microbial extracellular vesicles modulate the development of metabolic dysfunction-associated steatohepatitis through the gut-liver axis.

Metabolic dysfunction-associated steatohepatitis (MASH) represents a growing global health challenge due to its propensity to progress to irreversible...

FT-NIR and HPLC combined with machine learning for origin traceability and prediction of characteristic component content in Gastrodia elata.

As a dual-purpose plant with both medicinal and culinary applications, Gastrodia elata (GE) benefits from origin traceability and content prediction t...

Transcriptomic Plasticity Is a Hallmark of Metastatic Pancreatic Cancer.

UNLABELLED: Metastasis is the leading cause of cancer deaths. To develop strategies for intercepting metastatic progression, a better understanding of...

Photon-counting Detector CT Spectral Reconstructions for Radiomics-based Liver Lesion Classification: A Multicenter Study.

OBJECTIVES: Accurate noninvasive classification of hepatic lesions remains a diagnostic challenge, particularly on conventional CT. Photon Counting De...

Dosimetry Analysis of 177Lu-PSMA-I&T in Patients with Low-Volume Oligometastatic Hormone-Sensitive Prostate Cancer: A Secondary Analysis of the LUNAR Trial.

The phase 2 LUNAR trial randomized (1:1) patients with oligorecurrent hormone-sensitive prostate cancer to neoadjuvant [177Lu]Lu-PSMA-I&T (2 cycles, 6...

Multimodal AI model for early detection of hepatocellular carcinoma.

Detection of early hepatocellular carcinoma (eHCC) is important for timely treatment and improved prognosis. However, it is challenging to distinguish...

Machine learning-based DNA microarray analysis for disease detection using the MICRO-AI framework.

DNA microarray is a transformative technique in genomics, enabling simultaneous examination of thousands of gene expression levels. However, noise, hi...

A minimalist and robust diagnostic model for neonatal biliary atresia: Harnessing MMP-7 and machine learning in a time-critical setting.

BACKGROUND: Early diagnosis is the most critical determinant of native liver survival in infants with biliary atresia (BA). Accurate differentiation o...

Construction and validation of a prediction model for textbook outcome in distal cholangiocarcinoma undergoing pancreaticoduodenectomy based on six machine learning algorithms.

BACKGROUND: Textbook outcome (TO) serves as a validated composite metric for short-term surgical quality in pancreaticoduodenectomy (PD) patients. Thi...

Complex biological systems analysis and deep learning for prognostic prediction of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) prognosis remains poor, and traditional models often fail to capture complex nonlinear interactions between ...

Old Dogs Can Learn New Tricks: Artificial Intelligence Improves Adenoma Detection Rates in Screening Colonoscopies in Experienced Endoscopists.

BACKGROUND: A high adenoma detection rate in screening colonoscopy is associated with decreased rates of post-colonoscopy colorectal cancer. The use o...

Performance of Large Language Models vs Conventional Machine Learning for Predicting Clinical Outcomes With Limited Data: Comparative Study.

BACKGROUND: Machine learning (ML) can be used to predict clinical outcomes. Training predictive models typically requires data for hundreds or thousan...

ResTransUNet: a dual-encoder hybrid network for automated liver segmentation in CT scans.

Precise delineation of the liver is essential for effective diagnosis and treatment planning in hepatocellular carcinoma, yet current clinical practic...