Gastroenterology

Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizing resource allocation. This study evaluates the application of machine learning (ML) models, particularly deep learning neural networks (DLNN), in pre...

28-day all-cause mortality in patients with alcoholic cirrhosis: a machine learning prediction model based on the MIMIC-IV.

To develop and validate a machine learning prediction model for 28-day all-cause mortality in patients with alcoholic cirrhosis using data from the MIMIC-IV database. The data of 2134 patients diagnosed with alcoholic cirrhosis (AC) were obtained from Medical Information Mart for Intensive Care IV database. Machine learning algorithms, including decision trees, random forests, extreme gradient boo...

Machine learning driven biomarker selection for medical diagnosis.

Recent advances in experimental methods have enabled researchers to collect data on thousands of analytes simultaneously. This has led to correlationa...

Evaluation of artificial-intelligence-based liver segmentation and its application for longitudinal liver volume measurement.

BACKGROUND: Accurate liver-volume measurements from CT scans are essential for treatment planning, particularly in liver resection cases, to avoid pos...

Robotic Central Pancreatectomy with Omental Pedicle Flap: Tactics and Tips.

BACKGROUND: Robotic central pancreatectomy is increasingly used for pre- or low-grade malignant tumors in the pancreatic body balancing preservation o...

Evaluation of AI-Based Chatbots in Liver Cancer Information Dissemination: A Comparative Analysis of GPT, DeepSeek, Copilot, and Gemini.

BACKGROUND/OBJECTIVES: This study aimed to evaluate AI-based chatbots (GPT, DeepSeek, Copilot, Gemini) in disseminating information on liver cancer, e...

Copper Metabolism-Related Genes as Biomarkers in Colon Adenoma and Cancer.

PURPOSE: To elucidate the role of copper (Cu) metabolism in the progression of colon adenoma (CA) to colorectal cancer (CRC) and to identify potential...

Multimodal Artificial Intelligence Using Endoscopic USG, CT, and MRI to Differentiate Between Serous and Mucinous Cystic Neoplasms.

Introduction Serous cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) often exhibit similar imaging features when evaluated with a single ima...

Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.

Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing significant risks to human health. Despite their low envi...

Patient-specific deep learning tracking for real-time 2D pancreas localisation in kV-guided radiotherapy.

BACKGROUND AND PURPOSE: In pancreatic stereotactic body radiotherapy (SBRT), accurate motion management is crucial for the safe delivery of high doses...

Machine learning based gut microbiota pattern and response to fiber as a diagnostic tool for chronic inflammatory diseases.

Gut microbiota has been implicated in the pathogenesis of multiple gastrointestinal (GI) and systemic metabolic and inflammatory disorders where disru...

Histopathologic deep learning model for predicting tumor response to hepatic arterial infusion chemotherapy plus TKIs and ICIs in large hepatocellular carcinoma.

BACKGROUND: While triplet therapy (HTI), which combines hepatic arterial infusion chemotherapy (HAIC) with tyrosine kinase inhibitors and immune check...

Long-term exposure to PM and liver cancer mortality: Insights into the role of smaller particulate fractions.

Particulate matter (PM) is a recognized carcinogen, but the effects of PM on liver cancer remain underexplored. This study investigates the long-term ...

Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning.

The pancreas is a gland in the abdomen that helps to produce hormones and digest food. The irregular development of tissues in the pancreas is termed ...

Detecting genetic interactions with visible neural networks.

Non-linear interactions among single nucleotide polymorphisms (SNPs), genes, and pathways play an important role in human diseases, but identifying th...

Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study.

BACKGROUND: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multit...

Deep learning model applied to real-time delineation of colorectal polyps.

BACKGROUND: Deep learning models have shown considerable potential to improve diagnostic accuracy across medical fields. Although YOLACT has demonstra...

The Reverse Red-Green-Blue Rule: A Color-Coded Approach for Simplified Achalasia Diagnosis via High-Resolution Manometry.

BACKGROUND: Achalasia is a rare motility disorder of the esophagus. The diagnosis involves clinical suspicion based on history details and results of ...

Machine Learning Modeling for Predicting Infliximab Pharmacokinetics in Pediatric and Young Adult Patients With Crohn Disease: Leveraging Ensemble Modeling With Synthetic and Real-World Data.

BACKGROUND: Predicting infliximab pharmacokinetics (PK) is essential for optimizing individualized dosing in pediatric patients with Crohn disease (CD...

Artificial intelligence for early gastric cancer boundary recognition in NBI and nF-NBI endoscopic images.

OBJECTIVES: Precise delineation of early gastric cancer (EGC) margins is essential for complete resection during endoscopic submucosal dissection. Thi...