Latest AI and machine learning research in gastroenterology for healthcare professionals.
It is clear that artificial intelligence-based chatbots will be popular applications in the field of healthcare in the near future. It is known that more than 30% of the world's population suffers from chronic pain and individuals try to access the health information they need through online platforms before applying to the hospital. This study aimed to examine the readability, reliability and qua...
Background: Automated analysis of CT scans for abdominal organ measurement is crucial for improving diagnostic efficiency and reducing inter-observer variability. Manual segmentation and measurement of organs such as the kidneys, liver, spleen, and prostate are time-consuming and subject to inconsistency, underscoring the need for automated approaches. Purpose: The purpose of this study is to ...
Pancreatic ductal adenocarcinoma (PDAC) is one of the most common and aggressive types of pancreatic cancer. However, due to the lack of early and d...
Foodborne gastrointestinal (GI) illness is a common cause of ill health in the UK. However, many cases do not interact with the healthcare system, p...
Although Vision Transformers (ViTs) have recently demonstrated superior performance in medical imaging problems, they face explainability issues sim...
The incidence of gastrointestinal cancers remains significantly high, particularly in China, emphasizing the importance of accurate prognostic asses...
BACKGROUND: Accurate prediction of early recurrence (ER) is essential to improve the prognosis of patients with hepatocellular carcinoma (HCC) underwe...
This paper explores the application of reinforcement learning to optimize the parameters of a Type-1 Takagi-Sugeno fuzzy controller, designed to ope...
The Segment Anything Model (SAM) has revolutionized open-set interactive image segmentation, inspiring numerous adapters for the medical domain. How...
The scanning time for a fully sampled MRI can be undesirably lengthy. Compressed sensing has been developed to minimize image artifacts in accelerat...
Chronic superficial gastritis (CSG) severely affects quality of life and can progress to worse gastric pathologies. Traditional Chinese Medicine (TC...
Liver-vessel segmentation is an essential task in the pre-operative planning of liver resection. State-of-the-art 2D or 3D convolution-based methods...
High-throughput sequencing technologies have facilitated a deeper exploration of prognostic biomarkers. While many deep learning (DL) methods primaril...
The complementary information found in different modalities of patient data can aid in more accurate modelling of a patient's disease state and a bett...
The rapid advancement of next-generation sequencing (NGS) technology and the expanding availability of NGS datasets have led to a significant surge in...
Cancer is a major public health problem while liver cancer is the main cause of global cancer-related deaths. The previous study demonstrates that the...
BACKGROUND: The Mayo endoscopic subscore (MES) is an important quantitative measure of disease activity in ulcerative colitis. Colonoscopy reports in ...
Deep learning-based computer-aided diagnosis (CAD) of medical images requires large datasets. However, the lack of large publicly available labeled ...
Endoscopy serves as an essential procedure for evaluating the gastrointestinal (GI) tract and plays a pivotal role in identifying GI-related disorde...
Real-time acquisition of accurate depth of scene is essential for automated robotic minimally invasive surgery, and stereo matching with binocular e...