Gastroenterology

Deep learning for abdominal ultrasound: A computer-aided diagnostic system for the severity of fatty liver.

BACKGROUND: The prevalence of nonalcoholic fatty liver disease is increasing over time worldwide, with similar trends to those of diabetes and obesity. A liver biopsy, the gold standard of diagnosis, is not favored due to its invasiveness. Meanwhile, noninvasive evaluation methods of fatty liver are still either very expensive or demonstrate poor diagnostic performances, thus, limiting their appli...

Extraperitoneal Single-Port Robot-Assisted Radical Prostatectomy.

Robot-assisted radical prostatectomy (RARP) is currently the standard minimally invasive procedure for the surgical management of localized prostate cancer. It has been shown that the minimally invasive robotic approach offers comparable oncologic and functional outcomes with potential advantages, including decreased blood loss, shorter hospital stay, and recovery period when compared with open su...

[Ⅰ. Robot-Assisted Transmediastinal Esophagectomy for Esophageal Cancer].

Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network.

OBJECTIVE: Capsule endoscopy (CE) is pivotal for evaluation of small bowel disease. Obscure gastrointestinal bleeding most often originates from the s...

[Application of Deep Learning Reconstruction Algorithm in Low-Dose Thin-Slice Liver CT of Healthy Volunteers].

OBJECTIVE: To explore the clinical feasibility of applying deep learning (DL) reconstruction algorithm in low-dose thin-slice liver CT examination of ...

Radiomics and machine learning applications in rectal cancer: Current update and future perspectives.

The high incidence of rectal cancer in both sexes makes it one of the most common tumors, with significant morbidity and mortality rates. To define th...

[Chinese expert consensus on intracorporeal digestive reconstruction after robotic gastrectomy (2021 edition)].

The robotic surgical system applied to gastrectomy is regarded as a safe technique which has similar short- and long-term outcomes compared to laparos...

Establishment and validation of a computer-assisted colonic polyp localization system based on deep learning.

BACKGROUND: Artificial intelligence in colonoscopy is an emerging field, and its application may help colonoscopists improve inspection quality and re...

Transanal Minimally Invasive Surgery: A Useful Technique That Continues to Evolve.

Colorectal cancer remains the 3rd most common cancer diagnosed among men and women in the United States. With improved screening, premalignant rectal ...

Artificial Intelligence in Imaging of Chronic Liver Diseases: Current Update and Future Perspectives.

Here we review artificial intelligence (AI) models which aim to assess various aspects of chronic liver disease. Despite the clinical importance of he...

Radiogenomic and Deep Learning Network Approaches to Predict Mutation from Radiotherapy Plan CT.

BACKGROUND/AIM: We aimed to investigate the role of radiogenomic and deep learning approaches in predicting the KRAS mutation status of a tumor using ...

Letter: predictive model for gastric cancer after eradication of Helicobacter pylori-a survival analysis using a deep learning algorithm. Authors' reply.

Letter: predictive model for gastric cancer after eradication of Helicobacter pylori-a survival analysis using a deep learning algorithm.

Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic...

Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions.

The widespread availability of high-dimensional electronic healthcare record (EHR) datasets has led to significant interest in using such data to deri...

The Use of Readily Available Longitudinal Data to Predict the Likelihood of Surgery in Crohn Disease.

BACKGROUND: Although imaging, endoscopy, and inflammatory biomarkers are associated with future Crohn disease (CD) outcomes, common laboratory studies...

A graph auto-encoder model for miRNA-disease associations prediction.

Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identi...

Accurate diagnosis of endoscopic mucosal healing in ulcerative colitis using deep learning and machine learning.

BACKGROUND: In clinical applications, mucosal healing is a therapeutic goal in patients with ulcerative colitis (UC). Endoscopic remission is associat...

Application of artificial intelligence-driven endoscopic screening and diagnosis of gastric cancer.

The landscape of gastrointestinal endoscopy continues to evolve as new technologies and techniques become available. The advent of image-enhanced and ...

Status quo and future prospects of artificial neural network from the perspective of gastroenterologists.

Artificial neural networks (ANNs) are one of the primary types of artificial intelligence and have been rapidly developed and used in many fields. In ...