Faced with increasingly complex clinical situations, nurses must respond with accurate clinical judgment. But del Bueno (2005) reports that only 35 percent of new graduate nurses exhibit entry-level expectations of the necessary critical-thinking skills. Croskerry (2003) argues that clinicians' education should be directed at developing cognitive strategies that reduce errors in clinical decision-making. A challenge for nurse educators is finding activities to help students analyze their thinking as they address clinical problems. The author describes an assignment, given to third-year baccalaureate students, that used both online learning and high-fidelity patient simulation. Through discussions with instructors and peers, as well as personal reflection, students gained insight into both their sound and faulty critical thinking and clinical decisions.
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Br J Radiol
January 2025
2nd Department of Radiology, University General Hospital "ATTIKON", Medical School, National and Kapodistrian University of Athens, Greece.
In a rapidly evolving healthcare environment, artificial intelligence (AI) is transforming diagnostic techniques and personalised medicine. This is also seen in osseous biopsies. AI applications in radiomics, histopathology, predictive modelling, biopsy navigation, and interdisciplinary communication are reshaping how bone biopsies are conducted and interpreted.
View Article and Find Full Text PDFElectromagn Biol Med
January 2025
Department of Mathematics, University of Gour Banga, Malda, India.
In cardiovascular research, electromagnetic fields generated by Riga plates are utilized to study or manipulate blood flow dynamics, which is particularly crucial in developing treatments for conditions such as arterial plaque deposition and understanding blood behavior under varied flow conditions. This research predicts the flow patterns of blood enhanced with gold and maghemite nanoparticles (gold-maghemite/blood) in an electromagnetic microchannel influenced by Riga plates with a temperature gradient that decays exponentially, under sudden changes in pressure gradient. The flow modeling includes key physical influences like radiation heat emission and Darcy drag forces in porous media, with the flow mathematically represented through unsteady partial differential equations solved using the Laplace transform (LT) method.
View Article and Find Full Text PDFRepositioning a patient from the prone to supine position can delay the initiation of cardiopulmonary resuscitation (CPR). Investigators used high-fidelity simulation to assess the time to initiate chest compressions and the time during which compressions did not occur for supine and prone CPR. Sixty participants completed a knowledge assessment before and after attending an education session and completing two simulations (ie, supine, prone).
View Article and Find Full Text PDFJ Comput Graph Stat
October 2023
Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA.
Mixture Markov Model (MMM) is a widely used tool to cluster sequences of events coming from a finite state-space. However, the MMM likelihood being multi-modal, the challenge remains in its maximization. Although Expectation-Maximization (EM) algorithm remains one of the most popular ways to estimate the MMM parameters, however, convergence of EM algorithm is not always guaranteed.
View Article and Find Full Text PDFEar Hear
January 2025
San Francisco Department of Otolaryngology - Head and Neck Surgery, University of California, San Francisco, California, USA.
Objectives: Cochlear implant (CI) user functional outcomes are challenging to predict because of the variability in individual anatomy, neural health, CI device characteristics, and linguistic and listening experience. Machine learning (ML) techniques are uniquely poised for this predictive challenge because they can analyze nonlinear interactions using large amounts of multidimensional data. The objective of this article is to systematically review the literature regarding ML models that predict functional CI outcomes, defined as sound perception and production.
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