AIMC Topic: Digestive System Diseases
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An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).
Scientific reports
Apr 16, 2025
The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, remains a challenge. The Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) ( http://www.gutrhythm.com/public_database ) is a new source of el...
Drug-Related Side Effects and Adverse Reactions
Humans
Gastrointestinal Tract
Reproducibility of Results
Constipation
Deep Learning
ROC Curve
Big Data
Area Under Curve
Diarrhea
Feasibility Studies
Biological Clocks
Electrodiagnosis
Digestive System Diseases
Predictive Learning Models
Nausea
Vomiting
Databases, Pharmaceutical
Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.
Cancer genetics
Dec 22, 2024
CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-related immune responses exhibit diverse characteristics in different diseases. This study utilizes g...
Optimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes.
Liver international : official journal of the International Association for the Study of the Liver
May 31, 2024
Large Language Models (LLMs) are transformer-based neural networks with billions of parameters trained on very large text corpora from diverse sources. LLMs have the potential to improve healthcare due to their capability to parse complex concepts an...
Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning-Based Reconstruction of the Liver: Comparison to Conventional Free-Breathing Turbo Spin Echo.
Investigative radiology
Dec 26, 2022
OBJECTIVES: The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with co...
Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity.
Academic radiology
Jul 6, 2022
RATIONALE AND OBJECTIVES: To investigate the impact of a prototypical deep learning-based super-resolution reconstruction algorithm tailored to partial Fourier acquisitions on acquisition time and image quality for abdominal T1-weighted volume-interp...
Fast and accurate automated recognition of the dominant cells from fecal images based on Faster R-CNN.
Scientific reports
May 14, 2021
Fecal samples can easily be collected and are representative of a person's current health state; therefore, the demand for routine fecal examination has increased sharply. However, manual operation may pollute the samples, and low efficiency limits t...
Artificial intelligence and upper gastrointestinal endoscopy: Current status and future perspective.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Feb 14, 2019
With recent breakthroughs in artificial intelligence, computer-aided diagnosis (CAD) for upper gastrointestinal endoscopy is gaining increasing attention. Main research focuses in this field include automated identification of dysplasia in Barrett's ...
Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models.
World journal of gastroenterology
Dec 28, 2024
BACKGROUND: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology. However, the complexity of the digestive ...
[Development and thoughts of digestive endoscopy in children].
Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics
Apr 15, 2022
After nearly 40 years of development, digestive endoscopy in children has been widely applied, and it has helped to expand the spectrum of pediatric digestive system diseases and greatly improve the diagnosis and treatment of pediatric digestive syst...
Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.
The Lancet. Digital health
Feb 1, 2021
BACKGROUND: Ocular changes are traditionally associated with only a few hepatobiliary diseases. These changes are non-specific and have a low detection rate, limiting their potential use as clinically independent diagnostic features. Therefore, we ai...
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