Gastroenterology

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 toxicity and should therefore be monitored. We aimed to develop a machine learning model to identify those patients that need closer monitoring, enabling a safer and more efficient service.

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medical images. Yet, there is limited success on prediction of treatment response and outcomes, which has important implications for personalized treatment strategies. A significant hurdle for clinical translation of current data-driven deep learning models is lack of interpretability, often attributabl...

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 forces and chemical reactions in order to release nutr...

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 deep learning, have enabled the extraction of patho...

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 diabetes (T2D) and related traits. Despite these su...

De novo drug design based on patient gene expression profiles via deep learning.

Computational de novo drug design is a challenging issue in medicine, and it is desirable to consider all of the relevant information of the biologica...

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 at a community tertiary care hospital.

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 adaptive statistical iterative reconstruction-Veo (ASIR-V...

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 calculation of the liver segmental volume ratio (LSVR) o...

-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-risk patients and potential adverse reactions hav...

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 confirmed by increasing studies about gastric cancer (...

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 minimally invasive surgery. It is necessary to recogniz...

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 comparison to the Eastern Cooperative Oncology Grou...

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

The adoption of minimally invasive techniques for hepatocellular resection has progressively increased in North America. Cumulative evidence has demon...

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) and modified albumin-bilirubin (mALBI) grade both...

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 consistently reported. Our aim was to evaluate whether FLD...

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). Soft 3D fibrin gel allows efficient selection and gro...

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) and B cell receptors (BCRs), and their cognate anti...