The Institute of Medicine has identified both computerized physician order entry and electronic prescription as keys to reducing medication errors and improving safety. Many computerized clinical decision support systems can enhance practitioner performance. However, the development of such systems involves a long cycle time that makes it difficult to apply them on a wider scale. This paper presents a suite of guideline modeling and execution tools, built on Protégé, Jess and Java technologies, which are easy to use, and also capable of automatically synthesizing clinical decision support systems for clinical practice guidelines of moderate complexity.
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http://dx.doi.org/10.1016/j.cmpb.2010.05.010 | DOI Listing |
Clin Chim Acta
January 2025
Department of Rheumatism and Immunology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei 050000, PR China. Electronic address:
Background: Antiphospholipid Syndrome (APS) is a systemic autoimmune disorder characterized by arterial or venous thrombosis and/or pregnancy complications. This study aims to develop a diagnostic model for Obstetric APS (OAPS) using the Support Vector Machine (SVM) algorithm.
Methods: Data were retrospectively collected from 102 patients with OAPS and 80 healthy controls (HC).
Neural Netw
December 2024
Department of Computer Science, the University of Sheffield, UK.
Prompt learning is a powerful technique that enables the transfer of Vision-Language Models (VLMs) like CLIP to downstream tasks. However, when the prompt-based methods are fine-tuned solely on base classes, they often struggle to generalize to novel classes lacking visual samples during training, especially in scenarios with limited training data. To address this challenge, we propose an innovative approach called Synth-CLIP that leverages synthetic data to enhance CLIP's generalization capability for base classes and the general capability for novel classes.
View Article and Find Full Text PDFMidwifery
December 2024
Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia.
Problem And Background: Gestational diabetes mellitus (GDM) is a common medical complication of pregnancy, and the emerging evidence demonstrates how GDM online communities have a positive impact on promoting self-management and improving outcomes. Further analysis of such groups can increase understanding of how peer support in GDM online communities is enabled and enacted.
Aim: To examine women's experiences of GDM online communities on Facebook, their motivations for participation, and perceptions of dynamics within the community.
Seizure
November 2024
Neuronostics, Bristol, United Kingdom; Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham B15 2TT, United Kingdom; Institute of Metabolism and Systems Research, University of Birmingham, Birmingham B15 2TT, United Kingdom.
Background: Brain network analysis is an emerging field of research that could lead to the development, testing and validation of novel biomarkers for epilepsy. This could shorten the diagnostic uncertainty period, improve treatment, decrease seizure risk and lead to better management. This scoping review summarises the current state of electroencephalogram (EEG)-based network abnormalities for childhood epilepsies.
View Article and Find Full Text PDFJ Tissue Viability
January 2025
College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China. Electronic address:
Background: Diabetic nephropathy (DN) is a severe complication of diabetes mellitus and a leading cause of end-stage renal disease worldwide. Understanding trends in experimental research on DN is crucial for advancing knowledge and clinical management.
Objective: This study aimed to explore current trends in DN related experimental research, utilizing CiteSpace, VOSviewer, and Bibliometrix to identify key contributors, influential countries, and noteworthy topics.
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