Gastroenterology

Machine Learning-Based Pathomics Signature in Predicting MSH2 Expression and Prognosis in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) is one of the most prevalent and lethal gastrointestinal malignancies. MutS homolog 2 (MSH2), a DNA mismatch repair protein, has emerged as a promising prognostic biomarker. However, traditional histopathological evaluation is limited by restricted fields compared with whole-slide imaging. This study aimed to investigate whether machine learning-derived digital path...

How to predict abnormal acid reflux: recent developments.

INTRODUCTION: Recent advances in physiology and technology have led to the identification of additional parameters that have the potential to enhance diagnostic accuracy and inform the management of Gastroesophageal reflux disease (GERD). Whilst traditional pH monitoring and acid exposure time (AET) remain central to diagnosis, recent advances have introduced novel physiological markers that impro...

Nanoparticle approaches for hepatitis therapy and clinical translation.

BACKGROUND: Hepatitis B and C viruses (HBV and HCV) remain major global health challenges, contributing significantly to liver-related morbidity and m...

Evaluating the role of ChatGPT in structured radiology reporting: A systematic review.

BACKGROUND: The integration of large language models (LLMs) such as ChatGPT into radiology has introduced new possibilities for structured reporting. ...

Network for Real-time Laryngeal Lesions Video Object Detection.

Early and accurate diagnosis of nasopharyngeal-laryngeal tumors is critical for improving patient prognosis. Deep learning methods have achieved signi...

Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques.

BACKGROUND: Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating bet...

Label-free serum SERS combined with RFE-GBDT algorithm for non-invasive screening of liver cancer.

Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnos...

Reliable detection of Host-Microbe Signatures in cancer using PRISM.

Recent controversy in the cancer microbiome field highlights the need for more reliable microbial detection from human genomic data. Here, we develop ...

Shear stress optimization and smart control strategies toward AI-integrated tissue culture systems.

Shear stress serves as a key physical stimulus in three-dimensional (3D) cell culture systems, regulating critical physiological processes such as cel...

Auto-LSN: fully automated liver surface nodularity quantification in CT based on deep learning for the evaluation of advanced chronic liver disease.

OBJECTIVES: Liver surface nodularity (LSN) is a recognized non-invasive biomarker of cirrhosis. This study introduces auto-LSN, an artificial intellig...

Interpretable AI-driven prediction of early postoperative recurrence in locally advanced rectal cancer using the Systemic Inflammatory-Nutritional Index (SINTI): A multi-center study and clinical web tool.

BACKGROUND: Patients with locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (NCRT) and subsequently experience early rec...

Dual elastography ultrasound for classifying metabolic dysfunction-associated steatotic liver disease: a cross-sectional study within a prospective cohort.

BACKGROUND: The binary diagnostic approach does not reflect the entire spectrum of metabolic dysfunction associated steatotic liver disease (MASLD. We...

Evaluation of deliverable dose-mimicking automated volumetric arc radiation therapy planning for stage III non-small cell lung cancer patients: comparison with a commercial DVH-predicted automated planning system.

This study aimed to evaluate the clinical validity of a dose-mimicking automated planning for volumetric-modulated arc therapy (VMAT) in patients with...

Controversies in Computer-Assisted Detection in Colonoscopy.

BACKGROUND: Artificial intelligence (AI) applications in endoscopy, particularly computer-aided detection (CADe), have shown consistent benefit in ran...

AI-enhanced robotic hands: a breakthrough in early tumour detection and removal.

AI-enhanced robotic hands are rapidly reshaping tumour surgery by merging real-time sensing, precision mechanics, and intelligent decision support, ye...

Optimizing vedolizumab therapy in ulcerative colitis: A critical synthesis of trial evidence and the emerging role of artificial intelligence.

BACKGROUND: Vedolizumab, a monoclonal antibody targeting the α4β7 integrin, offers gut-selective immunosuppression and represents a cornerstone biolog...

Factors and determinants of primary care to tertiary care referrals in Singapore: A multi-centre analysis using artificial intelligence-powered large language models.

BACKGROUND: As Singapore adopts a population health approach under Healthier Singapore (Healthier SG), optimizing healthcare resources is crucial. We ...

Biological aging across the metabolic dysfunction-associated steatotic liver disease spectrum: A systematic review.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health burden. Geroscience posits that accel...

Prevalence of intestinal parasites in a tertiary care hospital and utility of AI-assisted fecal analyzer for their detection.

INTRODUCTION: Intestinal parasitic infections, caused by protozoa and helminths, can lead to malnutrition, anaemia, and impaired growth. While direct ...

Exploratory identification of intestinal health and productive performance patterns in post-weaning piglets using explainable machine learning.

Weaning is a critical stage in swine production, characterized by intestinal alterations that affect piglet health and performance. In this study, mac...