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Background: To evaluate the clinical value of foetal intelligent navigation echocardiography (5D Heart) for the display of key diagnostic elements in basic sections.
Methods: 3D volume datasets of 182 normal singleton foetuses were acquired with a four chamber view by using a volume probe. After processing the datasets by using 5D Heart, eight cardiac diagnostic planes were demonstrated, and the image qualities of the key diagnostic elements were graded by 3 doctors with different experiences in performing foetal echocardiography.
Results: A total of 231 volume datasets acquired from the 182 normal foetuses were used for 5D Heart analysis and display. The success rate of 8 standard diagnostic views was 88.2%, and the success rate of each diagnostic view was 55.8-99.2% and 70.7-99.0% for the random four chamber view as the initial section and for the apical four chamber view as the initial section, respectively. The success rate of each diagnostic element in the 8 diagnostic sections obtained by 5D Heart was 58.9%~ 100%. Excellent agreement was found between experienced sonographers and less-experienced sonographers (kappa> 0.769). Inter- and intra-observer agreement were substantial to near-perfect, kappa values ranging from 0.612 to 1.000 (Cohen's kappa).
Conclusions: 5D Heart can significantly improve the image quality of key diagnostic elements in foetal echocardiography with low operator dependency and good reproducibility.
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http://dx.doi.org/10.1186/s12880-020-00429-8 | DOI Listing |
Neural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
View Article and Find Full Text PDFTalanta
September 2025
Faculty of Applied Sciences, Ton Duc Thang University, Ho Chi Minh City, Viet Nam. Electronic address:
Food spoilage poses a global challenge with far-reaching consequences for public health, economic stability, and environmental sustainability. Conventional analytical methods for spoilage detection though accurate are often cost-prohibitive, labor-intensive, and unsuitable for real-time or field-based monitoring. Microfluidic paper-based analytical devices (μPADs) have emerged as a transformative technology offering rapid, portable, and cost-effective solutions for food quality assessment.
View Article and Find Full Text PDFJMIR Med Inform
September 2025
Department of Hepatobiliary and Vascular Surgery, First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Background: Primary liver cancer, particularly hepatocellular carcinoma (HCC), poses significant clinical challenges due to late-stage diagnosis, tumor heterogeneity, and rapidly evolving therapeutic strategies. While systematic reviews and meta-analyses are essential for updating clinical guidelines, their labor-intensive nature limits timely evidence synthesis.
Objective: This study proposes an automated literature screening workflow powered by large language models (LLMs) to accelerate evidence synthesis for HCC treatment guidelines.
JMIR Hum Factors
September 2025
College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
Background: The rapid advancement of next-generation sequencing has significantly expanded the landscape of precision medicine. However, health care professionals face increasing challenges in keeping pace with the growing body of oncological knowledge and integrating it effectively into clinical workflows. Precision oncology decision support (PODS) tools aim to assist clinicians in navigating this complexity, yet their current functionalities only partially address clinical needs.
View Article and Find Full Text PDFJ Med Internet Res
September 2025
Chulalongkorn University, Bangkok, Thailand.
Background: The interprofessional educational curriculum for patient and personnel safety is of critical importance, especially in the context of the COVID-19 pandemic, to prepare junior multiprofessional teams for emergency settings.
Objective: This study aimed to evaluate the effectiveness of an innovative interprofessional educational curriculum that integrated medical movies, massive open online courses (MOOCs), and 3D computer-based or virtual reality (VR) simulation-based interprofessional education (SimBIE) with team co-debriefing to enhance interprofessional collaboration and team performance using Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS). This study addressed 3 key questions.