Transcriptomics has revolutionized our understanding of the pathobiologic heterogeneity underlying complex allergic diseases, leading to both the discovery of multiple inflammatory allergic disease en...
Speckle tracking echocardiography (STE)-derived measures of myocardial mechanics, referred to herewithin as strain measurements, directly assess myocardial contractility and provide a nuanced assessme...
Strain measurements are advancing understanding of how cardiac dysfunction occurs in children with acquired and congenital heart disease (CHD). Global strain measurements can detect early changes in c...
Strain measurements provide a more detailed assessment of ventricular function than conventional measures of echocardiographic functional assessment. Strain measurements are increasingly being used to...
Nursing students collaborate and make clinical decisions in simulation scenarios. However, the literature does not clearly define the concept of peer collaborative clinical decision-making (PCCDM). Th...
A total of 19 articles were reviewed, and 11 dyads of nursing students were interviewed after participating in virtual reality simulation for their perspectives on PCCDM....
Five major themes were identified: group (1) communication; (2) awareness; (3) regulation; (4) reasoning; and (5) emotion. The conceptual definition of PCCDM is a dynamic, nonhierarchical, and group-l...
This analysis provides a conceptual definition of PCCDM in nursing simulation as well as a pathway for developing a theoretical framework and instrument....
The manner in which heuristics and biases influence clinical decision-making has not been fully investigated and the methods previously used have been rudimentary....
Two studies were conducted to design and test a trial-based methodology to assess the influence of heuristics and biases; specifically, with a focus on how practitioners make decisions about suitabili...
Study 1 (...
Experimental manipulations used to evoke heuristics did not significantly bias CDS. Decision-making style was not consistently associated with CDS. Clinical decisions were generally normative, althoug...
Clinical decision-making can be 'noisy' (i.e. variable across practitioners and occasions), but there was little evidence that this variability was systematically influenced by anchoring and halo effe...
Since the beginning of 2023, ChatGPT emerged as a hot topic in healthcare research. The potential to be a valuable tool in clinical practice is compelling, particularly in improving clinical decision ...
A prospective, cross-sectional study was designed based on an idea suggested by ChatGPT to assess the level of agreement between ChatGPT and five otorhinolaryngologists (ENTs) in 20 reality-inspired c...
The mean score of ChatGPT-1 was 4.4 (SD 1.2; min 1, max 5) and of ChatGPT-2 was 4.15 (SD 1.3; min 1, max 5), while the ENTs mean score was 4.91 (SD 0.3; min 3, max 5). The Mann-Whitney U test revealed...
Artificial intelligence will be an important instrument in clinical decision-making in the near future and ChatGPT is the most promising chatbot so far. Despite needing further development to be used ...
Predicting clinical events and providing assisted decision-making using Electronic Health Records (EHRs) play a central role in personalized healthcare. Despite the promising performance achieved for ...
The framework consists of two primary modules: (1) dual medical ontology representation learning to facilitate the learning of medical concepts and (2) task dependent multi-task prediction to capture ...
Experiments conducted on the MIMIC-III dataset show that the proposed model achieves the best performance, with a top-20 accuracy of 58.20% for diagnosis prediction and a top-20 accuracy of 75.85% for...
We propose an end-to-end cooperative dual medical ontology representation learning framework, which achieves superior performance on multi-task diagnosis and procedure predictions. The source code is ...
This study reveals the learning gained by Canadian and Rwandan nursing students from a course to enhance cross cultural clinical decision-making skills using a collaborative approach across two countr...
A qualitative descriptive study was conducted using thematic analysis. The study included analysis of end of course reflections of 94 students....
Students became more open-minded, curious, strengthening teamwork, increasing their critical thinking, and identifying cross-cultural similarities in practice. They challenged their previous beliefs a...
Students achieved a transformation of previous knowledge and decision-making skills. Results indicate the value of underpinning courses with theories and being open in allowing students to develop the...
Creating learning environments designed to stimulate open mindedness and exploration of cultures among students can be achieved through online learning. Providing opportunities for students to learn a...
Lymph node enlargement is common in children, with 90% of physiologically palpable lymph nodes. This study aimed to develop a predictive model based on clinical characteristics to enhance the diagnosi...
A clinical prediction rule was developed using a retrospective, cross-sectional design for patients under 15 years who underwent lymph node biopsy from 2012 to 2022. Multivariable risk regression was ...
Of 188 children, 70 (37.2%) had benign lymphadenopathy beyond reactive hyperplasia, and 27 (14.4%) had malignant lymphadenopathy. The predictive model included 12 characteristics such as size, locatio...
The model demonstrated reasonably accurate predictions for the clinical characteristics of pediatric lymphadenopathy. It tended to overestimate malignancy but did not miss diagnoses, aiding in reducin...
The continued demand for digital health requires that providers adapt thought processes to enable sound clinical decision-making in digital settings. Providers report that lack of training is a barrie...
The development of computational methodologies to support clinical decision-making is of vital importance to reduce morbidity and mortality rates. Specifically, prescriptive analytic is a promising ar...
In this study, we propose a methodology for the development of prescriptive models to support decision-making in clinical settings. The prescriptive model requires a predictive model to build the pres...
The performance of the developed prescriptive models demonstrated the ability to estimate warfarin doses in coagulated patients, prescribe treatment for severe dengue and generate actions aimed at the...
The developed models performed well to prescribe actions aimed to monitor, treat and prevent diseases. This type of strategy allows supporting decision-making in clinical settings. However, validation...
