Yang and Qiu proposed and reframed an expected utility-entropy (EU-E) based decision model. Later on, a similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation. Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rating funds. Furthermore, we evaluate the performance of the fund ratings based on the EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.
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http://dx.doi.org/10.3390/e23040481 | DOI Listing |
N Z Med J
January 2025
Executive Dean, Bond Business School, Bond University, Gold Coast, QLD, Australia; Harkness Senior Fellow, Commonwealth Fund of New York.
This article makes the case for taking a model-based management approach, specifically using the Viable System Model (VSM), to embed learning and adaptation into the New Zealand health system so it can function as a learning health system. We draw on a case study of a specialist clinical service where the VSM was used to guide semi-structured interviews and workshops with clinicians and managers and to guide analysis of the findings. The VSM analysis revealed a lack of clarity of organisational functioning, and of the systems, processes and integrated IT infrastructure necessary to support the fundamental requirements of a learning health system.
View Article and Find Full Text PDFShock
January 2025
Department of Industrial and Systems Engineering, University of Florida, P.O. Box 116595, Gainesville, FL, 32611, USA.
Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to ICUs of Mayo Clinic Hospitals over eight-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status.
View Article and Find Full Text PDFPLoS Biol
January 2025
Cognitive Control Collaborative, University of Iowa, Iowa City, Iowa, United States of America.
Practice not only improves task performance but also changes task execution from rule- to memory-based processing by incorporating experiences from practice. However, how and when this change occurs is unclear. We test the hypothesis that strategy transitions in task learning can result from decision-making guided by cost-benefit analysis.
View Article and Find Full Text PDFPLoS Biol
January 2025
Carney Institute for Brain Science, Department of Cognitive & Psychological Sciences, Brown University, Providence, Rhode Island, United States of America.
The basal ganglia (BG) play a key role in decision-making, preventing impulsive actions in some contexts while facilitating fast adaptations in others. The specific contributions of different BG structures to this nuanced behavior remain unclear, particularly under varying situations of noisy and conflicting information that necessitate ongoing adjustments in the balance between speed and accuracy. Theoretical accounts suggest that dynamic regulation of the amount of evidence required to commit to a decision (a dynamic "decision boundary") may be necessary to meet these competing demands.
View Article and Find Full Text PDFPLoS One
January 2025
Jinan University, Guangzhou, China.
Objective: This study aimed to develop and validate a nomogram to predict the risk of sepsis in non-traumatic subarachnoid hemorrhage (SAH) patients using data from the MIMIC-IV database.
Methods: A total of 803 SAH patients meeting the inclusion criteria were randomly divided into a training set (563 cases) and a validation set (240 cases). Independent prognostic factors were identified through forward stepwise logistic regression, and a nomogram was created based on these factors.
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