Gastroenterology

Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma.

BACKGROUND: Deep learning is promising to predict treatment response. We aimed to evaluate and valid...

Deep Learning for Automated Liver Segmentation to Aid in the Study of Infectious Diseases in Nonhuman Primates.

With the advent of deep learning, convolutional neural networks (CNNs) have evolved as an effective ...

Quantitative determination of D-cystine in mice using LC-MS/MS and its application to the assessment of pharmacokinetics and bioavailability.

Cystine is the primary source material for the synthesis of glutathione. However, the pharmacokineti...

Preliminary exploration of robotic complete mesocolic excision for colon cancer with the domestically produced Chinese minimally invasive Micro Hand S surgical robot system.

OBJECTIVE: To summarize our initial experience with robot-assisted complete mesocolic excision (R-CM...

Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors.

BACKGROUND: Although endoscopic ultrasound (EUS) is reported to be suitable for determining the laye...

CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer.

PURPOSE: This work aimed to develop and validate a deep learning radiomics model for evaluating sero...

Incorporating standardised reporting guidelines in clinical trials of artificial intelligence in gastrointestinal endoscopy.

Transcervical (SP) and Transhiatal DaVinci Robotic Esophagectomy: A Cadaveric Study.

BACKGROUND: This is a preclinical cadaveric study to investigate the feasibility of a fully robotic ...

Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.

Fifty years of research on the nature of backscatter from tissues has resulted in a number of promis...

Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.

Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-...

Artificial intelligence technology applications in the pathologic diagnosis of the gastrointestinal tract.

Artificial intelligence (AI) is a complex technology with a steady flow of new applications, includi...

Application of optical character recognition with natural language processing for large-scale quality metric data extraction in colonoscopy reports.

BACKGROUND AND AIMS: Colonoscopy is commonly performed for colorectal cancer screening in the United...

Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.

Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, th...

Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach.

Oral bioavailability (OBA)-related pharmacokinetic properties, such as aqueous solubility, lipophili...

Deep learning-based lumbosacral reconstruction for difficulty prediction of percutaneous endoscopic transforaminal discectomy at L5/S1 level: A retrospective cohort study.

BACKGROUND: Deep learning has been validated as a promising technique for automatic segmentation and...

Assessment of a Deep Learning Model to Predict Hepatocellular Carcinoma in Patients With Hepatitis C Cirrhosis.

IMPORTANCE: Deep learning, a family of machine learning models that use artificial neural networks, ...

Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network.

BACKGROUND: Although great advances in artificial intelligence for interpreting small bowel capsule ...

ASO Author Reflections: Clinical Benefit of Robot-Assisted Minimally Invasive Esophagectomy over Conventional Minimally Invasive Esophagectomy.

Multi-level feature aggregation network for instrument identification of endoscopic images.

Identification of surgical instruments is crucial in understanding surgical scenarios and providing ...

Robotic "Double Loop" Roux-en-Y gastric bypass reduces the risk of postoperative internal hernias: a prospective observational study.

BACKGROUND: Internal herniation (IH) is a potentially serious complication after laparoscopic Roux-e...

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimiz...