Gastroenterology

Use of large language models as clinical decision support tools for management pancreatic adenocarcinoma using National Comprehensive Cancer Network guidelines.

BACKGROUND: Large language models may form the basis of clinical decision support tools to improve rates of guideline concordant care for pancreatic ductal adenocarcinoma. The objectives of this study were to 1) define the first-pass accuracy of 2 publicly available large language models in responding to prompts on the basis of National Comprehensive Cancer Network guidelines for pancreatic ductal...

Controlling nutritional status score predicts posthepatectomy liver failure: an online interpretable machine learning prediction model.

BACKGROUND AND AIMS: Posthepatectomy liver failure (PHLF) remains a severe complication after hepatectomy for hepatocellular carcinoma (HCC) and accurate preoperative evaluation and predictive measures are urgently needed. We investigated the impact of the controlling nutritional status (CONUT) score on PHLF and utilized machine learning (ML) algorithms to identify high-risk individuals of PHLF.

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to mortality. We developed a recurrence prediction s...

Indication model for laparoscopic repeat liver resection in the era of artificial intelligence: machine learning prediction of surgical indication.

BACKGROUND: Laparoscopic repeat liver resection (LRLR) is still a challenging technique and requires a careful selection of indications. However, the ...

Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.

BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellular carcinoma (HCC) remains challenging. Nonetheles...

Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre clinical study.

To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional en...

Vision-language large learning model, GPT4V, accurately classifies the Boston Bowel Preparation Scale score.

INTRODUCTION: Large learning models (LLMs) such as GPT are advanced artificial intelligence (AI) models. Originally developed for natural language pro...

Factor enhanced DeepSurv: A deep learning approach for predicting survival probabilities in cirrhosis data.

BACKGROUND: Over the years, various models, including both traditional and machine learning models, have been employed to predict survival probabiliti...

Machine learning analysis identified NNMT as a potential therapeutic target for hepatocellular carcinoma based on PCD-related genes.

Programmed cell death (PCD) plays a critical role in cancer biology, influencing tumor progression and treatment response. This study aims to investig...

Explainable machine learning model for predicting acute pancreatitis mortality in the intensive care unit.

BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with acute pancreatitis (AP); this might be improved b...

Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol.

BACKGROUND: Mild acute biliary pancreatitis (MABP) presents significant clinical and economic challenges due to its potential for relapse. Current gui...

Machine Learning-Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study.

BACKGROUND: Early complications increase in-hospital stay and mortality after intestinal obstruction surgery. It is important to identify the risk of ...

Enhancing DILI toxicity prediction through integrated graph attention (GATNN) and dense neural networks (DNN).

Drug-induced liver injury (DILI) toxicity is a condition when drugs have a destructive effect on the liver organ. The prediction of this toxicity beco...

Diagnostic accuracy of convolutional neural network algorithms to distinguish gastrointestinal obstruction on conventional radiographs in a pediatric population.

PURPOSE: Gastrointestinal (GI) dilatations are frequently observed in radiographs of pediatric patients who visit emergency departments with acute sym...

Improving the Real-Time Classification of Disease Severity in Ulcerative Colitis: Artificial Intelligence as the Trigger for a Second Opinion.

INTRODUCTION: Endoscopic classification of ulcerative colitis (UC) shows high interobserver variation. Previous research demonstrated that artificial ...

ieGENES: A machine learning method for selecting differentially expressed genes in cancer studies.

Gene selection is crucial for cancer classification using microarray data. In the interests of improving cancer classification accuracy, in this paper...

Machine Learning-Based Mortality Prediction for Acute Gastrointestinal Bleeding Patients Admitted to Intensive Care Unit.

OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patients with acute gastrointestinal bleeding (AGIB) in...

Multi-parametric MRI Habitat Radiomics Based on Interpretable Machine Learning for Preoperative Assessment of Microsatellite Instability in Rectal Cancer.

RATIONALE AND OBJECTIVES: This study constructed an interpretable machine learning model based on multi-parameter MRI sub-region habitat radiomics and...

Artificial intelligence in endoscopic diagnosis of esophageal squamous cell carcinoma and precancerous lesions.

Esophageal squamous cell carcinoma (ESCC) poses a significant global health challenge, necessitating early detection, timely diagnosis, and prompt tre...

Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.

INTRODUCTION: Hydrogel spacers (HS) are designed to minimise the radiation doses to the rectum in prostate cancer radiation therapy (RT) by creating a...