Gastroenterology

Global trends in artificial intelligence applications for gastric cancer prediction, treatment, and management: a topic modeling and bibliometric analysis.

PURPOSE: Artificial intelligence (AI) emerged as a promising tool for enhancing healthcare delivery and outcomes for gastric cancer (GC) patients. This study aimed to analyze research development, patterns, and trends in AI applications on GC. METHODS: In total, 1,854 publications from the Web of Science database (1993-2024) were extracted. Text-mining and bibliometric tools were employed to exami...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tissues. Prostate cancer ranks as one of the most prevalent malignancies among men globally, particularly in regions with high human development indices. The disease often progresses silently in its early stages, underscoring the critical need for timel...

Integrating multiphase MRI surrogates to improve microvascular invasion detection and recurrence risk stratification in HCC.

BACKGROUND & AIMS: Microvascular invasion (MVI) is a key determinant of recurrence and poor outcomes in hepatocellular carcinoma (HCC), yet accurate p...

Lipidomic machine learning predictor for progression of gastric cancer.

BACKGROUND: Gastric cancer (GC) is a leading cause of global cancer mortality, characterized by aggressive progression and poor prognosis. The develop...

M3Hep: a multimodal hepatotoxicity prediction model combining mitochondrial toxicity and masking strategy.

Drug hepatotoxicity is one of the primary reasons for drug clinical trial failures and market withdrawals, with mitochondrial dysfunction being one of...

Bridging tradition and innovation: Acupuncture for depression through clinical efficacy and neurobiological insights.

BACKGROUND: To elucidate the research progress on acupuncture therapy as a complementary and alternative medicine treatment for depression by reviewin...

GICAF-Net: A cross-attentional graph-image fusion network for hyperspectral pathological diagnosis of FNH and HCC.

BACKGROUND AND OBJECTIVE: Accurate intraoperative differentiation between focal nodular hyperplasia (FNH) and hepatocellular carcinoma (HCC) remains a...

Combined dual-phase CT radiomics and deep transfer learning model for oxaliplatin response in unresectable colorectal liver metastases.

OBJECTIVES: Accurate prediction of response to first-line oxaliplatin-based chemotherapy in unresectable colorectal liver metastases (CRLM) is critica...

Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP.

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare ...

Abdominal multi-organ segmentation on 3D negative-contrast CT cholangiopancreatography: a comparative study of deep learning methods.

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCT...

Unsupervised machine learning for identifying morphological phenotypes in abdominal aortic aneurysms using fully automated volume-segmented imaging: a multicentre cohort study.

AIMS: Thrombo- and microembolic complications following abdominal aortic aneurysm (AAA) repair are hypothesized to be associated with wall thrombus bu...

Deep-Learning Virtual Superior Mesenteric Artery Modeling for Risk Stratification in Pancreas Surgery.

BACKGROUND: Understanding the patient-specific anatomy of the superior mesenteric artery (SMA) and its branches is of critical importance when perform...

White Light, Magnifying Endoscopy, Endocytoscopy, and Artificial Intelligence in Diagnosis of Early Colorectal Cancer: A Comparative Study.

OBJECTIVES: Early detection of colorectal cancer is critical for improving prognosis. However, assessing invasion depth-distinguishing between superfi...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Observation and Localization in CT Images.

Pancreatic cancer remains one of the deadliest malignancies, primarily because of its subtle CT appearance and frequent late-stage diagnosis. We intro...

Colonoscopy Quality and Strategies for Improvement.

Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscop...

Artificial intelligence in colon cancer: A commentary on advances and challenges.

Artificial intelligence-driven CT radiomics model predicts prognosis in TACE-refractory hepatocellular carcinoma.

PURPOSE: To develop an integrated predictive model combining radiomics, clinical risk factors, and machine learning for prognostic assessment in hepat...

A CT-based 2.5D deep learning model for preoperative T-staging in gastric cancer: a retrospective multicenter study.

PURPOSE: To develop and validate a 2.5D multi-angle deep learning (MADL) model for preoperative T-staging in patients with gastric cancer (GC) and to ...

Intelligent ensemble learning-enhanced finite element modeling for precision thermal ablation in cancer therapy.

BACKGROUND: Microwave ablation (MWA) is a minimally invasive treatment for liver tumors, yet accurate prediction of ablation zones remains challenging...

Translating Gut Microbiota into Diagnostics: A Multidimensional Approach for the Diagnosis of Inflammatory Bowel Disease.

The gut microbiota has emerged as a key factor in the pathophysiology of inflammatory bowel disease (IBD), providing novel opportunities for diagnosti...