Gastroenterology

Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy is a conserved cellular mechanism that selectively removes damaged mitochondria and is crucial for cellular homeostasis. While tumor development and resistance to anticancer therapies are related to ESCC, their role in ESCC remains unclear. Here, we investigated the relationship between mitophagy-rel...

Review of Deep Learning Performance in Wireless Capsule Endoscopy Images for GI Disease Classification.

Wireless capsule endoscopy is a non-invasive medical imaging modality used for diagnosing and monitoring digestive tract diseases. However, the analysis of images obtained from wireless capsule endoscopy is a challenging task, as the images are of low resolution and often contain a large number of artifacts. In recent years, deep learning has shown great promise in the analysis of medical images, ...

Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection.

BACKGROUND: Unplanned reoperation (URO) after surgery adversely affects the quality of life and prognosis of patients undergoing anterior resection fo...

AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting antiviral treatment.

BACKGROUND & AIMS: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, follow-up after sustained ...

Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.

Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the p...

Characterizing the Coefficient of Friction Between a Capsule Robot and the Colon.

OBJECTIVE: A capsule robot (CR) with an onboard active locomotion mechanism, has been developed as a promising alternative to colonoscopy due to its m...

Predictive modeling of hepatitis B viral dynamics: a caputo derivative-based approach using artificial neural networks.

A fractional model for the kinetics of hepatitis B transmission was developed. The hepatitis B virus significantly affects the world's economic and he...

Automated gall bladder cancer detection using artificial gorilla troops optimizer with transfer learning on ultrasound images.

The gallbladder (GB) is a small pouch and a deep tissue placed under the liver. GB Cancer (GBC) is a deadly illness that is complex to discover in an ...

Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medi...

Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.

BACKGROUND: Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects pat...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artificial intelligence-based cecum recognition system ...

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning.

Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD) is a unique form of programmed cell death that i...

Development and validation of a machine learning-based framework for assessing metabolic-associated fatty liver disease risk.

BACKGROUND: The existing predictive models for metabolic-associated fatty liver disease (MAFLD) possess certain limitations that render them unsuitabl...

The role of artificial intelligence and image processing in the diagnosis, treatment, and prognosis of liver cancer: a narrative-review.

Artificial intelligence (AI) and image processing are revolutionising the diagnosis and management of liver cancer. Recent advancements showcase AI's ...

Improved diagnostic efficiency of CRC subgroups revealed using machine learning based on intestinal microbes.

BACKGROUND: Colorectal cancer (CRC) is a common cancer that causes millions of deaths worldwide each year. At present, numerous studies have confirmed...

Deep Learning Algorithm‑Based MRI Radiomics and Pathomics for Predicting Microsatellite Instability Status in Rectal Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: To develop and validate multimodal deep-learning models based on clinical variables, multiparametric MRI (mp-MRI) and hemato...

Will Transformers change gastrointestinal endoscopic image analysis? A comparative analysis between CNNs and Transformers, in terms of performance, robustness and generalization.

Gastrointestinal endoscopic image analysis presents significant challenges, such as considerable variations in quality due to the challenging in-body ...

Deciphering the cytotoxicity of micro- and nanoplastics in Caco-2 cells through meta-analysis and machine learning.

Plastic pollution, driven by micro- and nanoplastics (MNPs), poses a major environmental threat, exposing humans through various routes. Despite human...

Use machine learning to predict pulmonary metastasis of esophageal cancer: a population-based study.

BACKGROUND: This study aims to establish a predictive model for assessing the risk of esophageal cancer lung metastasis using machine learning techniq...

Diagnostic application of the ColonFlag AI tool in combination with faecal immunochemical test in patients on an urgent lower gastrointestinal cancer pathway.

OBJECTIVE: Colorectal cancer (CRC) is the fourth most common cancer in the UK. Patients with symptoms suggestive of CRC should be referred for urgent ...