Knowledge acquisition for the design of clinical decision support systems can be facilitated when clinical practice guidelines serve as a knowledge source. We describe application of the Guideline Elements Model (GEM) in the design of a decision support system to promote smoking cessation. Following selection of relevant recommendations and markup of knowledge components with the GEM Cutter editor, the Extractor stylesheet was used to create a list of decision variables and actions for further processing. Decision variables and actions that reflect similar concepts were consolidated. Action types were identified. Extracting the critical concepts from the narrative text facilitates clarification of necessary content. The guideline-centric approach promotes accurate translation of guideline knowledge.
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Scand J Trauma Resusc Emerg Med
January 2025
PreHospen-Centre for Prehospital Research, Faculty of Caring Science, Work Life and Social Welfare, University of Borås, Borås, Sweden.
Introduction: Chest pain is one of the most common reasons for contacting the emergency medical services (EMS). It is difficult for EMS personnel to distinguish between patients suffering from a high-risk condition in need of prompt hospital care and patients suitable for non-conveyance. A vast majority of patients with chest pain are therefore transported to the emergency department (ED) for further investigation even if hospital care is not necessary.
View Article and Find Full Text PDFReprod Biol Endocrinol
January 2025
Departments of Internal Medicine and Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, 330 Cedar St, New Haven, CT, 06510, USA.
Background: Overweight and obesity-chronic illnesses in which an increase in body fat promotes adipose tissue dysfunction and abnormal fat mass resulting in adverse metabolic, biomechanical, and psychosocial health consequences-negatively impact female fertility. Adverse conception outcomes are multifactorial, ranging from poor oocyte quality and implantation issues to miscarriages and fetal health issues. However, with the advent of novel pharmacologic agents, significant weight loss can be achieved, improving the chances of healthy pregnancies, and their use should be considered during periconceptual counseling.
View Article and Find Full Text PDFBMC Public Health
January 2025
Núcleo de Avaliação de Tecnologias em Saúde, Grupo de Pesquisa Clínica e Políticas Públicas em Doenças Infecciosas e Parasitárias, Instituto René Rachou, Fundação Oswaldo Cruz, Avenue Augusto de lima, 1715, Barro Preto, Belo Horizonte, MG, 30190-009, Brazil.
Background: Open government data (OGD) in the health sector consolidates transparency, access to information, and collaboration between the government and different sectors of society. It is an essential instrument for health systems and researchers to generate initiatives, drive innovations, and qualify decision-making, whether in health emergencies or supporting the creation of more effective public policies. This review aimed to identify OGD initiatives in healthcare and their possible applications.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
Dental age estimation, as an important part of forensic anthropology, has a wide range of applications for its results in legal practice. Given the lowered legal age for criminal responsibility in China and the increasing juvenile delinquency, we establish a morphological database targeting the second (M2) and third molars (M3) of the Southern Chinese population. Full mouth orthopantomography from 1486 individuals aged 8.
View Article and Find Full Text PDFSci Rep
January 2025
Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran.
Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.
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