Gastroenterology

Indocyanine green-based fluorescence imaging improved by deep learning.

Intraoperative identification of malignancies using indocyanine green (ICG)-based fluorescence imagi...

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of ...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forc...

An overview of ultrasound-derived radiomics and deep learning in liver.

Over the past few years, developments in artificial intelligence (AI), especially in radiomics and d...

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 d...

Implementation of robotic pancreaticoduodenectomy at a community tertiary care hospital utilizing a comprehensive curriculum.

BACKGROUND: We evaluated the outcomes of a robotic pancreaticoduodenectomy (RPD) program implemented...

A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results.

This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptiv...

Automated liver segmental volume ratio quantification on non-contrast T1-Vibe Dixon liver MRI using deep learning.

PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calcul...

-derived postbiotics inhibited digestion of triglycerides, glycerol phospholipids and sterol lipids allosteric regulation of BSSL, PTL and PLA2 to prevent obesity: perspectives on deep learning integrated multi-omics.

The anti-obesity potential of probiotics has been widely reported, however their utilization in high...

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been conf...

Usefulness of real-time navigation using intraoperative ultrasonography for rectal cancer resection.

INTRODUCTION: At our institute, we usually perform robot-assisted surgery for rectal cancer as minim...

Robotic anterior resection and partial peritonectomy for rectal cancer with peritoneal carcinomatosis-A video vignette.

Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.

OBJECTIVES: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in c...

Minimally Invasive Robotic Techniques for Hepatocellular Carcinoma Resection: How I Do It.

The adoption of minimally invasive techniques for hepatocellular resection has progressively increas...

Bleeding at the root of the inferior mesenteric artery during robotic D3 lymph node dissection for rectal cancer - a video vignette.

A novel combined C-reactive protein-albumin ratio and modified albumin-bilirubin score can predict long-term outcomes in patients with hepatocellular carcinoma after hepatic resection.

BACKGROUND: Systemic inflammatory response represented by C-reactive protein and albumin ratio (CAR)...

Decreased liver-to-spleen ratio in low-dose computed tomography as a biomarker of fatty liver disease reflects risk for myocardial ischaemia.

AIMS: A strong association between fatty liver disease (FLD) and coronary artery disease is consiste...

Hybrid AI models allow label-free identification and classification of pancreatic tumor repopulating cell population.

Human pancreatic cancer cell lines harbor a small population of tumor repopulating cells (TRCs). Sof...

DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis.

Structural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) a...

Identification of antigen-presentation related B cells as a key player in Crohn's disease using single-cell dissecting, hdWGCNA, and deep learning.

Crohn's disease (CD) arises from intricate intercellular interactions within the intestinal lamina p...

Non-invasive tumor microenvironment evaluation and treatment response prediction in gastric cancer using deep learning radiomics.

The tumor microenvironment (TME) plays a critical role in disease progression and is a key determina...