Automated classification of colorectal neoplasms in white-light colonoscopy images via deep learning
Background: Classification of colorectal neoplasms during colonoscopic examination is
important to avoid unnecessary endoscopic biopsy or resection. This study aimed to develop …
important to avoid unnecessary endoscopic biopsy or resection. This study aimed to develop …
Capsule endoscopy: Pitfalls and approaches to overcome
SH Kim, HJ Chun - Diagnostics, 2021 - mdpi.com
Capsule endoscopy of the gastrointestinal tract is an innovative technology that serves to
replace conventional endoscopy. Wireless capsule endoscopy, which is mainly used for …
replace conventional endoscopy. Wireless capsule endoscopy, which is mainly used for …
Performance and comparison of artificial intelligence and human experts in the detection and classification of colonic polyps
MD Li, ZR Huang, QY Shan, SL Chen, N Zhang… - BMC …, 2022 - Springer
Objective The main aim of this study was to analyze the performance of different artificial
intelligence (AI) models in endoscopic colonic polyp detection and classification and …
intelligence (AI) models in endoscopic colonic polyp detection and classification and …
A new approach for gastrointestinal tract findings detection and classification: Deep learning-based hybrid stacking ensemble models
Endoscopic procedures for diagnosing gastrointestinal tract findings depend on specialist
experience and inter-observer variability. This variability can cause minor lesions to be …
experience and inter-observer variability. This variability can cause minor lesions to be …
[HTML][HTML] Machine learning as a new horizon for colorectal cancer risk prediction? A systematic review
O Kennion, S Maitland, R Brady - Health Sciences Review, 2022 - Elsevier
Background Machine learning algorithms have demonstrated high performance in the risk
stratification of patients for colorectal cancer. Despite the promise, there has not yet been a …
stratification of patients for colorectal cancer. Despite the promise, there has not yet been a …
Artificial intelligence in colorectal cancer diagnosis using clinical data: non-invasive approach
Colorectal cancer is the third most common and second most lethal tumor globally, causing
900,000 deaths annually. In this research, a computer aided diagnosis system was …
900,000 deaths annually. In this research, a computer aided diagnosis system was …
Learning spatiotemporal features for esophageal abnormality detection from endoscopic videos
Esophageal cancer is categorized as a type of disease with a high mortality rate. Early
detection of esophageal abnormalities (ie precancerous and early cancerous) can improve …
detection of esophageal abnormalities (ie precancerous and early cancerous) can improve …
A framework with a fully convolutional neural network for semi-automatic colon polyp annotation
Deep learning has delivered promising results for automatic polyp detection and
segmentation. However, deep learning is known for being data-hungry, and its performance …
segmentation. However, deep learning is known for being data-hungry, and its performance …
Decision-making in artificial intelligence: is it always correct?
HS Kim - Journal of Korean Medical Science, 2020 - synapse.koreamed.org
Big data and artificial intelligence (AI), which apply big data, are still actively discussed in the
medical field. Diverse studies utilize big data with the goal of developing AI, 1-3 and there …
medical field. Diverse studies utilize big data with the goal of developing AI, 1-3 and there …
Development and validation of a meta-learning-based multi-modal deep learning algorithm for detection of peritoneal metastasis
Purpose The existing medical imaging tools have a detection accuracy of 97% for peritoneal
metastasis (PM) bigger than 0.5 cm, but only 29% for that smaller than 0.5 cm, the early …
metastasis (PM) bigger than 0.5 cm, but only 29% for that smaller than 0.5 cm, the early …