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Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.
Int J Cardiovasc Imaging
January 2025
Division of Cardiology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MPXA-2000) in lesion detection and quantification using manual QCA as the reference standard, and to demonstrate its superiority over visual estimation. This multi-center retrospective study analyzed 1,076 coronary angiography images obtained from 420 patients, comparing AI-QCA and visual estimation against manual QCA as the reference standard.
View Article and Find Full Text PDFComparing Operative Outcomes and Resection Quality in Robotic vs Open Pancreaticoduodenectomy: A Meta-analysis of 54,000 Patients.
J Gastrointest Cancer
January 2025
Dow University of Health Sciences, Karachi, Pakistan.
Background: High morbidity and mortality make pancreaticoduodenectomy (PD) one of the most complicated surgical procedures. This meta-analysis aimed to compare the outcomes of robotic pancreaticoduodenectomy (RPD) versus open pancreaticoduodenectomy (OPD).
Method: A comprehensive literature search of PubMed, Cochrane Central, and Google Scholar was conducted from inception to November 2024.
A large-scale dataset for Chinese historical document recognition and analysis.
Sci Data
January 2025
School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China.
The development of Chinese civilization has produced a vast collection of historical documents. Recognizing and analyzing these documents hold significant value for the research of ancient culture. Recently, researchers have tried to utilize deep-learning techniques to automate recognition and analysis.
View Article and Find Full Text PDFIdentification of Gingival Inflammation Surface Image Features Using Intraoral Scanning and Deep Learning.
Int Dent J
January 2025
Department of Stomatology, Beijing Tongren Hospital, Capital Medical University, Beijing, China. Electronic address:
Introduction And Aim: The assessment of gingival inflammation surface features mainly depends on subjective judgment and lacks quantifiable and reproducible indicators. Therefore, it is a need to acquire objective identification information for accurate monitoring and diagnosis of gingival inflammation. This study aims to develop an automated method combining intraoral scanning (IOS) and deep learning algorithms to identify the surface features of gingival inflammation and evaluate its accuracy and correlation with clinical indicators.
View Article and Find Full Text PDFA novel clinical investigation using deep learning and human-in-the-loop approach in orbital volume measurement.
J Craniomaxillofac Surg
January 2025
Department of Plastic and Reconstructive Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea. Electronic address:
Orbital volume assessment is crucial for surgical planning. Traditional methods lack efficiency and accuracy. Recent studies explore AI-driven techniques, but research on their clinical effectiveness is limited.
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