AIMC Topic: Precancerous Conditions
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Accuracy of artificial intelligence-assisted endoscopy in the diagnosis of gastric intestinal metaplasia: A systematic review and meta-analysis.
PloS one
May 14, 2024
BACKGROUND AND AIMS: Gastric intestinal metaplasia is a precancerous disease, and a timely diagnosis is essential to delay or halt cancer progression. Artificial intelligence (AI) has found widespread application in the field of disease diagnosis. Th...
An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research.
Head and neck pathology
May 10, 2024
INTRODUCTION: Oral epithelial dysplasia (OED) is a precancerous histopathological finding which is considered the most important prognostic indicator for determining the risk of malignant transformation into oral squamous cell carcinoma (OSCC). The g...
Deep learning assists detection of esophageal cancer and precursor lesions in a prospective, randomized controlled study.
Science translational medicine
Apr 17, 2024
Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection rate remains challenging. We developed a system based on deep convolutional neural networks (CNNs) fo...
Deep Learning in High-Resolution Anoscopy: Assessing the Impact of Staining and Therapeutic Manipulation on Automated Detection of Anal Cancer Precursors.
Clinical and translational gastroenterology
Apr 1, 2024
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell carcinoma (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising res...
Anal Canal
Acetic Acid
Adult
Proctoscopy
Squamous Intraepithelial Lesions
Sensitivity and Specificity
Male
Middle Aged
Predictive Value of Tests
Deep Learning
Female
Precancerous Conditions
Staining and Labeling
Carcinoma, Squamous Cell
Humans
Anus Neoplasms
Aged
Neural Networks, Computer
Algorithms
Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.
International journal of medical informatics
Mar 22, 2024
BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active inte...
OralEpitheliumDB: A Dataset for Oral Epithelial Dysplasia Image Segmentation and Classification.
Journal of imaging informatics in medicine
Feb 26, 2024
Early diagnosis of potentially malignant disorders, such as oral epithelial dysplasia, is the most reliable way to prevent oral cancer. Computational algorithms have been used as an auxiliary tool to aid specialists in this process. Usually, experime...
A deep learning model based on magnifying endoscopy with narrow-band imaging to evaluate intestinal metaplasia grading and OLGIM staging: A multicenter study.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Feb 23, 2024
BACKGROUND AND PURPOSE: Patients with stage III or IV of operative link for gastric intestinal metaplasia assessment (OLGIM) are at a higher risk of gastric cancer (GC). We aimed to construct a deep learning (DL) model based on magnifying endoscopy w...
A novel artificial intelligence-assisted gastric dysplasia detection model to streamline its removal via endoscopic submucosal dissection.
Gastrointestinal endoscopy
Jan 20, 2024
Artificial intelligence-aided diagnostic imaging: A state-of-the-art technique in precancerous screening.
Journal of gastroenterology and hepatology
Dec 7, 2023
BACKGROUND AND AIM: Chromoendoscopy with the use of indigo carmine (IC) dye is a crucial endoscopic technique to identify gastrointestinal neoplasms. However, its performance is limited by the endoscopist's skill, and no standards are available for l...
Editorial Comment: With Artificial Intelligence Applications, One Size Does Not Fit All.
AJR. American journal of roentgenology
Dec 6, 2023
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