Inflammatory Bowel Disease

Colorectal Cancer Detected by Machine Learning Models Using Conventional Laboratory Test Data.

Current diagnostic methods for colorectal cancer (CRC) are colonoscopy and sigmoidoscopy, which are...

[Application of artificial intelligence technology in the diagnosis and treatment of colorectal cancer].

The combination of artificial intelligence (AI) technology and medicine is an important milestone in...

A Case of Dapsone-induced Mild Methemoglobinemia with Dyspnea and Cyanosis.

Dear Editor, Dapsone is a dual-function drug with antimicrobial and antiprotozoal effects and anti-i...

Pathomics in urology.

PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is cu...

Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach.

OBJECTIVE: To identify important clinical or imaging features predictive of an individual's response...

Colon capsule endoscopy versus CT colonography after incomplete colonoscopy. Application of artificial intelligence algorithms to identify complete colonic investigations.

BACKGROUND: Guidelines suggest computed tomography colonography (CTC) following incomplete optical c...

Effectiveness of a Deep-learning Polyp Detection System in Prospectively Collected Colonoscopy Videos With Variable Bowel Preparation Quality.

BACKGROUND: Colonoscopy is the gold standard for polyp detection, but polyps may be missed. Artifici...

Using Computer-Aided Polyp Detection During Colonoscopy.

Artificial Intelligence for Understanding Imaging, Text, and Data in Gastroenterology.

Artificial intelligence (AI) could change the practice of gastroenterology through its ability to bo...

[Application of convolutional neural network to risk evaluation of positive circumferential resection margin of rectal cancer by magnetic resonance imaging].

To explore the feasibility of using faster regional convolutional neural network (Faster R-CNN) to ...

Development of Genome-Derived Tumor Type Prediction to Inform Clinical Cancer Care.

IMPORTANCE: Diagnosing the site of origin for cancer is a pillar of disease classification that has ...

Study on detection rate of polyps and adenomas in artificial-intelligence-aided colonoscopy.

BACKGROUND/AIM: To study the impact of computer-aided detection (CADe) system on the detection rate ...

[Rectal Gastrointestinal Stromal Tumor(GIST)Excised by Two Teams Following Neoadjuvant Chemotherapy-A Case Report].

A 67-year-old man presented with bloody stools. Colonoscopy showed a small submucosal tumor in the l...

Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets.

We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravas...

Ontologic Model of Diagnostics and Treatment of Gastrointestinal Bleedings of Unknown Origin.

The article presents the semantic model of diagnostics and treatment of patients with gastrointestin...

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); how...

Emerging next-generation robotic colonoscopy systems towards painless colonoscopy.

Advances in the field of robotics have allowed modern technology to be integrated into medicine and ...

Overview of Deep Learning in Gastrointestinal Endoscopy.

Artificial intelligence is likely to perform several roles currently performed by humans, and the ad...

Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

OBJECTIVES: The aim of this study was to test the ability of a commercially available natural langua...

Endometriosis Knowledgebase: a gene-based resource on endometriosis.

Endometriosis is a complex, benign, estrogen-dependent gynecological disorder with an incidence of ~...

Methodology to develop machine learning algorithms to improve performance in gastrointestinal endoscopy.

Assisted diagnosis using artificial intelligence has been a holy grail in medical research for many ...