Gastroenterology

Estimation of postmortem interval under different ambient temperatures based on multi-organ metabolomics and machine learning algorithm.

In forensic practice, the estimation of postmortem interval has been a persistent challenge. Recentl...

Future Perspectives of Liver Research in the Asia-Pacific Region: Focus on Hepatitis B and C.

The Asia-Pacific region faces serious liver health challenges, primarily because of the comparativel...

Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most cruc...

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) faci...

Recent progress in surgical treatment of cervical spine myelopathy - A narrative review.

Surgical techniques and technology for cervical spondylotic myelopathy (CSM) have demonstrated remar...

Machine learning-driven prognostic model based on sphingolipid-related gene signature in pancreatic cancer: development and validation.

BACKGROUND: Pancreatic cancer, a highly malignant tumor with poor prognosis, lacks effective early d...

The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalizat...

From development to implementation: a systematic review on the current maturity status of artificial intelligence models for patients with colorectal cancer liver metastases.

Introduction Artificial intelligence (AI) is increasingly being researched and developed in the medi...

Applications of artificial intelligence in abdominal imaging.

The rapid advancements in artificial intelligence (AI) carry the promise to reshape abdominal imagin...

Clinical significance of risk factor analysis in pancreatic cancer by using supervised model of machine learning.

INTRODUCTION: Pancreatic cancer (PC) poses a significant global health challenge due to its aggressi...

Identification of autophagy-related genes in intestinal ischemia-reperfusion injury and their role in immune infiltration.

BACKGROUND: Intestinal ischemia-reperfusion (II/R) injury is a serious condition characterized by hi...

Multidimensional Evidence Chain of Nutritional Impact on Digestive System Tumors: Integration of Mendelian Randomization Causal Inference, NHANES Epidemiological Data, and Transcriptomic Analysis.

BACKGROUND: The global burden of digestive system tumors (e.g., hepatocellular carcinoma, gastric ca...

Developing a predictive model for septic shock risk in acute pancreatitis patients using interpretable machine learning algorithms.

BACKGROUND: Septic shock is a severe complication of acute pancreatitis (AP), often associated with ...

Leveraging automated machine learning to predict colon cancer prognosis from clinical features and risk groups: a retrospective cohort study.

BACKGROUND: Predicting colon cancer recurrence is crucial for determining the need for adjuvant ther...

Developing a ground truth for a convolutional neural network-based segmentation of anatomical structures in endoscopic ear surgery videos.

OBJECTIVE: This study aimed to develop a ground truth for a convolutional neural network-based segme...

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enha...

Deep ensemble framework with Bayesian optimization for multi-lesion recognition in capsule endoscopy images.

In order to address the challenges posed by the large number of images acquired during wireless caps...

Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits pronounced heterogeneity, which significantly li...

Large language models for detecting colorectal polyps in endoscopic images.

CDKN1A and EGR1 are key genes for endoplasmic reticulum stress-induced ferroptosis in MASH.

Metabolic dysfunction-associated steatohepatitis (MASH) is a complex liver disease whose pathogenesi...

Advancing open-source visual analytics in digital pathology: A systematic review of tools, trends, and clinical applications.

Histopathology is critical for disease diagnosis, and digital pathology has transformed traditional ...