Inflammatory Bowel Disease

Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation.

To study the effect of computerized tomography (CT) images based on deep learning algorithms on the diagnosis of pulmonary nodules and the effect of radiofrequency ablation (RFA), the -shaped fully convolutional neural network (FCNN) (-Net) was enhanced. The convolutional neural network (CNN) algorithm was compared with the -Net algorithm, and segmentation performances were analyzed. Then, it was ...

Artificial Intelligence for Colonoscopy: Past, Present, and Future.

During the past decades, many automated image analysis methods have been developed for colonoscopy. Real-time implementation of the most promising methods during colonoscopy has been tested in clinical trials, including several recent multi-center studies. All trials have shown results that may contribute to prevention of colorectal cancer. We summarize the past and present development of colonosc...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate of patients is improved by early detection. With ...

Automated histological classification for digital pathology images of colonoscopy specimen via deep learning.

Colonoscopy is an effective tool to detect colorectal lesions and needs the support of pathological diagnosis. This study aimed to develop and validat...

Prediction of vedolizumab treatment outcomes by machine learning.

Codon Optimization Using a Recurrent Neural Network.

Codon optimization of a DNA sequence can significantly increase efficiency of protein expression, reducing the cost to manufacture biologic pharmaceut...

PRAPNet: A Parallel Residual Atrous Pyramid Network for Polyp Segmentation.

In a colonoscopy, accurate computer-aided polyp detection and segmentation can help endoscopists to remove abnormal tissue. This reduces the chance of...

Artificial intelligence implementation in pancreaticobiliary endoscopy.

INTRODUCTION: Artificial intelligence has been rapidly deployed in gastroenterology and endoscopy. The acceleration of deep convolutional neural netwo...

Simplified Machine Learning Models Can Accurately Identify High-Need High-Cost Patients With Inflammatory Bowel Disease.

INTRODUCTION: Hospitalization is the primary driver of inflammatory bowel disease (IBD)-related healthcare costs and morbidity. Traditional prediction...

Systematic review of artificial intelligence-based image diagnosis for inflammatory bowel disease.

OBJECTIVES: Diagnosis of inflammatory bowel diseases (IBD) involves combining clinical, laboratory, endoscopic, histologic, and radiographic data. Art...

Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion.

In clinical practice, automatic polyp segmentation from colonoscopy images is an effective assistant manner in the early detection and prevention of c...

Artificial Intelligence Improves Detection at Colonoscopy: Why Aren't We All Already Using It?

Artificial Intelligence for Inflammatory Bowel Diseases (IBD); Accurately Predicting Adverse Outcomes Using Machine Learning.

BACKGROUND: Inflammatory Bowel Diseases with its complexity and heterogeneity could benefit from the increased application of Artificial Intelligence ...

Detection and Classification of Colorectal Polyp Using Deep Learning.

Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required ...

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorect...

Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.

BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images acquired during colonoscopy may help colonoscopists...

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for ...

Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy.

Artificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. AI has led to several clinically approved algorithm...

The Role of Gabapentinoids in the Substance Use Pattern of Adult Germans Seeking Inpatient Detoxification Treatment - A Pilot Study.

To shed more light on the addictive power of the gabapentinoids (GPTs) gabapentin and pregabalin, we performed a structured face-to-face interview wit...

Graph-Based Region and Boundary Aggregation for Biomedical Image Segmentation.

Segmentation is a fundamental task in biomedical image analysis. Unlike the existing region-based dense pixel classification methods or boundary-based...