Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.6
3.6
Journals
Diagnostics
Special Issues
Modern Imaging and Computer-Aided Diagnosis in Gastroenterology, 2nd Edition
share announcement

Modern Imaging and Computer-Aided Diagnosis in Gastroenterology, 2nd Edition

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Optical Diagnostics".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 3416

Special Issue Editors

Prof. Dr. Costin Teodor Streba

E-Mail Website
Guest Editor
Department of Research Methodology, University of Medicine and Pharmacy of Craiova, 200533 Craova, Romania
Interests: artificial neural network; medical image analysis; biomedical image processing; medical image processing; biomedical image technologies; pulmonology; lung disease; gastroenterology; liver; pancreas; histology; computerized morphometry; microscopic image analysis; computer-assisted image analysis; cell image analysis
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Dan Ionuţ Gheonea

E-Mail
Guest Editor
Research Center of Gastroenterology and Hepatology, University of Medicine and Pharmacy of Craiova, Craiova, Romania
Interests: inflammatory bowel diseases; digestive cancers; endoscopic imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Novel endoscopic methods have significantly improved the diagnostic accuracy, minimally invasive therapy, and, ultimately, survival in many gastrointestinal (GI) diseases of the 21st century. High-yield methods for direct and indirect visualization of the GI tract and connected organs offer enhanced macroscopic and microscopic information for the physician. Significant improvements in imaging sensors and the possibility to use several methods in a single procedure have greatly reduced hospitalization times, and effective targeted therapies can be used to essentially eliminate the need for invasive surgery. On the other hand, artificial intelligence has the potential to completely change the landscape of medical diagnosis, especially in gastroenterology.

This Special Issue aims to gather a collection of diverse views on all novel imaging techniques in gastrointestinal endoscopy and connected imaging methods for rapid diagnosis and possible targeted treatment, with a focus on modern imaging and computer-aided diagnosis in gastroenterology.

Prof. Dr. Costin Teodor Streba
Prof. Dr. Dan Ionuţ Gheonea
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

15 pages, 877 KiB  
Article
The Accuracy of Pre-Endoscopic Scores for Mortality Prediction in Patients with Upper GI Bleeding and No Endoscopy Performed
by Sergiu Marian Cazacu, Dragoș Ovidiu Alexandru, Răzvan-Cristian Statie, Sevastița Iordache, Bogdan Silviu Ungureanu, Vlad Florin Iovănescu, Petrică Popa, Victor Mihai Sacerdoțianu, Carmen Daniela Neagoe and Mirela Marinela Florescu
Diagnostics 2023, 13(6), 1188; https://doi.org/10.3390/diagnostics13061188 - 21 Mar 2023
Cited by 1 | Viewed by 1538
Abstract
(1) Background: The assessment of mortality and rebleeding rate in upper gastrointestinal bleeding (UGIB) is essential, and several prognostic scores have been proposed. Some patients with UGIB did not undergo endoscopy, either because they refused the procedure, suffered from alcohol withdrawal symptoms or [...] Read more.
(1) Background: The assessment of mortality and rebleeding rate in upper gastrointestinal bleeding (UGIB) is essential, and several prognostic scores have been proposed. Some patients with UGIB did not undergo endoscopy, either because they refused the procedure, suffered from alcohol withdrawal symptoms or altered general status, or because the bleeding was severe enough to cause death before the endoscopy. The mortality risk in the subgroup of patients without endoscopy is poorly evaluated in the literature. (2) Methods: The purpose of the study was to identify the most useful scores for the assessment of in-hospital mortality in patients with UGIB with no endoscopy performed and no known etiology. A total of 198 patients with UGIB and no endoscopy performed were admitted between January 2017 and December 2021 and the accuracy of 12 prognostic scores and the Charlson comorbidity index for in-hospital mortality prediction were analyzed, as well as Child–Pugh Turcotte (CPT) and Meld scores in patients with cirrhosis. (3) Results: The mortality rate was 37.9%, higher than in variceal (21.9%, p < 0.0001) and non-variceal bleeding (7.4%, p < 0.0001). The most accurate scores by AUC were the International Bleeding score (INBS, 0.844), Glasgow Blatchford (0.783), MAP score (0.78), Iino (0.766), AIM65 and modified N-score (0.745 each), modified Glasgow-Blatchford (0.73), H3B2 and N-score (0.701); Rockall, Baylor, and T-score had an AUC below 0.7. MELD score was superior to CPT in patients with cirrhosis (AUC 0.811 versus 0.670). (4) Conclusions: The mortality rate in UGIB with no endoscopy was higher than in both variceal and non-variceal bleeding and was higher in the pandemic period but with no statistical significance (45.3% versus 32.14%, p = 0.0586), mainly because of positive cases. Only one case of rebleeding was noted; the hospitalization period was significantly shorter. The most accurate score was International Bleeding Score; the MELD score had a higher but moderate accuracy compared with CPT in patients with cirrhosis. Full article
(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology, 2nd Edition)
►▼ Show Figures

Figure 1

Review

Jump to: Research

18 pages, 638 KiB  
Review
The Importance of Artificial Intelligence in Upper Gastrointestinal Endoscopy
by Dusan Popovic, Tijana Glisic, Tomica Milosavljevic, Natasa Panic, Marija Marjanovic-Haljilji, Dragana Mijac, Milica Stojkovic Lalosevic, Jelena Nestorov, Sanja Dragasevic, Predrag Savic and Branka Filipovic
Diagnostics 2023, 13(18), 2862; https://doi.org/10.3390/diagnostics13182862 - 05 Sep 2023
Cited by 2 | Viewed by 1558
Abstract
Recently, there has been a growing interest in the application of artificial intelligence (AI) in medicine, especially in specialties where visualization methods are applied. AI is defined as a computer’s ability to achieve human cognitive performance, which is accomplished through enabling computer “learning”. [...] Read more.
Recently, there has been a growing interest in the application of artificial intelligence (AI) in medicine, especially in specialties where visualization methods are applied. AI is defined as a computer’s ability to achieve human cognitive performance, which is accomplished through enabling computer “learning”. This can be conducted in two ways, as machine learning and deep learning. Deep learning is a complex learning system involving the application of artificial neural networks, whose algorithms imitate the human form of learning. Upper gastrointestinal endoscopy allows examination of the esophagus, stomach and duodenum. In addition to the quality of endoscopic equipment and patient preparation, the performance of upper endoscopy depends on the experience and knowledge of the endoscopist. The application of artificial intelligence in endoscopy refers to computer-aided detection and the more complex computer-aided diagnosis. The application of AI in upper endoscopy is aimed at improving the detection of premalignant and malignant lesions, with special attention on the early detection of dysplasia in Barrett’s esophagus, the early detection of esophageal and stomach cancer and the detection of H. pylori infection. Artificial intelligence reduces the workload of endoscopists, is not influenced by human factors and increases the diagnostic accuracy and quality of endoscopic methods. Full article
(This article belongs to the Special Issue Modern Imaging and Computer-Aided Diagnosis in Gastroenterology, 2nd Edition)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop