Gastroenterology

Signature-aware deep learning reveals distinct driver gene programs and mutational processes in glioblastoma and colon adenocarcinoma.

The precise identification of cancer driver mutations is essential for precision oncology; however, ...

LCMS-Net: Deep Learning for Raw High Resolution Mass Spectrometry Data Applied to Forensic Cause-of-Death Screening.

Current preprocessing workflows for untargeted metabolomics using liquid chromatography-high resolut...

Towards deep-learning based detection and quantification of intestinal metaplasia on digitized gastric biopsies: a multi-expert comparative study.

Current gastric cancer (GCa) risk systems are prone to errors since they evaluate a visual estimatio...

From manual parametric to artificial intelligence-based automation: A systematic review of recent advances in endoscopic surgical skills evaluation.

Evaluating surgical skills is critical to surgical training. Numerous methods and scoring scales hav...

Evaluating deep learning models for pancreatic cancer diagnosis.

Pancreatic cancer is a highly aggressive and often fatal disease, with early detection being a key f...

Research progress of machine learning applications in gastric cancer diagnosis and therapy.

Gastric cancer (GC), a malignant neoplasm originating from the gastric mucosal epithelium, represent...

Ensemble model assisted classification of gastrointestinal bleeding using wireless capsule endoscopy.

Wireless Capsule Endoscopy (WCE) is a useful method for imaging the intestines painlessly and lookin...

Identification of Gene Signatures Differentiating Cancer from Normal Tissues Across Histological Classifications of Gastric Adenocarcinoma via Machine Learning Methods.

Gastric adenocarcinoma is a significant global health concern. Among the myriad histologic classific...

Diagnosis of Gastric Intestinal Metaplasia: Histology, Endoscopy, and Artificial Intelligence.

Background Gastric intestinal metaplasia (GIM) is a well-established precancerous lesion and key bio...

Endoscopic Ultrasound for the Management of Pancreatic Neuroendocrine Tumors: Diagnosis, Treatment, and Future Perspectives.

Pancreatic neuroendocrine tumors (PanNETs) are increasingly diagnosed, reflecting greater clinical a...

Explainable AI for mortality prediction: a comparative study using the MIMIC-III dataset.

OBJECTIVES: Predicting mortality is vital for tailoring treatments, improving care and reducing cost...

Development and validation of machine learning models for diagnosing hepatocellular carcinoma risk and survival in patients with diabetic cirrhosis.

Imputation methods for serologic biomarkers in inflammatory bowel disease.

Serologic biomarkers have emerged as a powerful tool for the diagnosis of Inflammatory Bowel Disease...

The Clinical Utility of Three-Dimensional Liver Modelling: A Multicenter Survey.

Pre-operative planning for complex liver surgery is constrained by 2D CT/MRI. Digital 3D liver model...

Comprehensive assessment of postoperative metachronous liver metastasis risk in colon cancer based on inflammatory indicators: a multicenter prospective study.

OBJECTIVE: Insidiousness is a hallmark of metachronous liver metastasis. Owing to the absence of a c...

An artificial intelligence-assisted comprehensive model for predicting lymph node metastasis in superficial esophageal squamous cell carcinoma: a diagnostic study.

BACKGROUND: Superficial esophageal squamous cell carcinoma (ESCC) is increasingly detected due to en...

Discovery of H2 Receptor Antagonists as Colistin Enhancers by Targeting Acid Stress Response.

Plasmid-mediated colistin resistance gene mcr has markedly diminished the effectiveness of colistin ...

External Validation of an AI-Based Colonoscopy Quality Assessment Tool in Japanese Clinical Practice: A Pilot Study.

BACKGROUND: While AI-assisted polyp detection has advanced significantly, comprehensive AI-based col...

A longitudinal cohort study: developing an interpretable machine learning model to predict incident depression risk in elderly Chinese patients with gastrointestinal or chronic liver diseases.

[Utilizing machine learning and SHAP analysis to develop a prognostic survival prediction model for gastric cancer patients following radical gastrectomy].

Objective: To construct a prediction model and website for the overall survival (OS) of gastric canc...

Microbial fuel cells for sustainable energy and wastewater treatment: Integrating seaweed biomass, machine learning, and hybrid systems for enhanced performance.

Seaweeds (SWs) have been widely used in food, agricultural, pharmaceutical industries, and biofuel p...