Latest AI and machine learning research in gastroenterology for healthcare professionals.
BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by active angiogenesis and heterogeneous vascular patterns. However, vascular pattern profiling in tumors and its clinical significance remain unexplored. OBJECTIVES: This study aimed to develop an artificial intelligence-based system for quantitative vascular pattern profiling in HCC and to investigate the associations between vascular p...
Purpose To develop a deep learning-enabled single breath-hold abbreviated MRI (DL-SBH-aMRI) protocol for hepatocellular carcinoma (HCC) diagnosis. Materials and Methods Patients at high risk of HCC from four institutions (January 2019-January 2025) were prospectively and retrospectively included. All patients underwent conventional complete MRI (cMRI) examinations including precontrast T1-weighted...
The management of febrile neutropenia (FN) in oncohematological patients is undergoing a paradigm shift driven by a deeper understanding of patients' ...
Accurate prediction of organ-specific toxicity with mechanistic interpretability remains a central challenge in chemical safety assessment and transla...
OBJECTIVE: Tumor budding (TB) is a histopathological marker of aggressive behavior and poor prognosis in rectal cancer (RC), yet not reliably evaluate...
OBJECTIVE: We aimed to propose a prognostic framework using a dual-branch Vision Transformer (ViT) deep learning (DL) architecture for stratifying rec...
Esophageal cancer is a highly aggressive malignancy where early detection is critical for survival. However, early-stage lesions typically present sub...
OBJECTIVES: This study evaluates the clinical utility of an artificial intelligence (AI)-driven volumetric approach for assessing treatment response i...
OBJECTIVES: To develop various artificial intelligence (AI) models including radiomics, deep transfer learning (DTL) and habitat analysis models, as w...
Distinguishing pancreatic ductal adenocarcinoma (PDAC) from mass-forming pancreatitis (MFP) is challenging due to imaging mimicry and reader-dependent...
BACKGROUND: Artificial intelligence (AI)-based anatomical recognition has emerged to support intraoperative cognition; however, its clinical utility b...
Deep learning (DL)-based pathological image modelling and analysis approaches offer transformative potential for early cancer diagnostics, yet limited...
Context-dependent alternative splicing plays a critical role in disease pathogenesis and organ development, but its complex regulation remains challen...
BACKGROUND: Lymph node metastasis (LNM) is an important prognostic factor but is often underdiagnosed due to limitations in conventional assessment me...
The rising disease burden of inflammatory bowel disease (IBD) parallels the changing dietary landscape accompanying industrialization, underscoring th...
BACKGROUND: Perforation following chemotherapy in gastrointestinal lymphoma (PFCGL) is a rare but severe and life-threatening complication. Early pre-...
Predicting spatial gene expression from hematoxylin and eosin (H&E)-stained histological images is a central challenge in the field of computational p...
BACKGROUND: Light is a significant environmental stimulus affecting embryonic development during incubation, and it is known that different wavelength...
BACKGROUND: Colorectal cancer (CRC) leads to heavy disease and economic burdens globally. Early screening such as colonoscopy has been demonstrated to...
OBJECTIVE: To systematically evaluate the diagnostic performance of artificial intelligence (AI) models for hepatocellular carcinoma (HCC) and to pool...