Objective: To provide a select review of our applications of quantitative modeling to highlight the utility of such approaches to better understand the neuropsychological deficits associated with various neurologic and psychiatric diseases.
Method: We review our work examining category learning in various patient populations, including individuals with basal ganglia disorders (Huntington's Disease and Parkinson's disease), amnesia and Eating Disorders.
Results: Our review suggests that the use of quantitative models has enabled a better understanding of the learning deficits often observed in these conditions and has allowed us to form novel hypotheses about the neurobiological bases of their deficits.
Conclusions: We feel that the use of neurobiologically inspired quantitative modeling holds great promise in neuropsychological assessment and that future clinical measures should incorporate the use of such models as part of their standard scoring. Appropriate studies need to be completed, however, to determine whether such modeling techniques adhere to the rigorous psychometric properties necessary for a valid and reliable application in a clinical setting. (PsycINFO Database Record
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http://dx.doi.org/10.1037/neu0000422 | DOI Listing |
NPJ Sci Learn
December 2024
Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Bandar Sunway, 475000, Malaysia.
This study evaluates the ability of large language models (LLMs) to deliver criterion-based grading and examines the impact of prompt engineering with detailed criteria on grading. Using well-established human benchmarks and quantitative analyses, we found that even free LLMs achieve criterion-based grading with a detailed understanding of the criteria, underscoring the importance of domain-specific understanding over model complexity. These findings highlight the potential of LLMs to deliver scalable educational feedback.
View Article and Find Full Text PDFSci Rep
December 2024
Bioinformatics Laboratory, College of Computing, University Mohammed VI Polytechnic, Ben Guerir, Morocco.
Hepatitis C virus (HCV) presents a significant global health issue due to its widespread prevalence and the absence of a reliable vaccine for prevention. While significant progress has been achieved in therapeutic interventions since the disease was first identified, its resurgence underscores the need for innovative strategies to combat it. The nonstructural protein NS5A is crucial in the life cycle of the HCV, serving as a significant factor in both viral replication and assembly processes.
View Article and Find Full Text PDFNat Commun
December 2024
School of Data Science, The Chinese University of Hong Kong-Shenzhen, Shenzhen, China.
Recently, RNA velocity has driven a paradigmatic change in single-cell RNA sequencing (scRNA-seq) studies, allowing the reconstruction and prediction of directed trajectories in cell differentiation and state transitions. Most existing methods of dynamic modeling use ordinary differential equations (ODE) for individual genes without applying multivariate approaches. However, this modeling strategy inadequately captures the intrinsically stochastic nature of transcriptional dynamics governed by a cell-specific latent time across multiple genes, potentially leading to erroneous results.
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December 2024
Department of Mathematics, GC University, Lahore, Pakistan.
In this article, a nonlinear fractional bi-susceptible [Formula: see text] model is developed to mathematically study the deadly Coronavirus disease (Covid-19), employing the Atangana-Baleanu derivative in Caputo sense (ABC). A more profound comprehension of the system's intricate dynamics using fractional-order derivative is explored as the primary focus of constructing this model. The fundamental properties such as positivity and boundedness, of an epidemic model have been proven, ensuring that the model accurately reflects the realistic behavior of disease spread within a population.
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December 2024
Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences, Tehran, Iran.
No study has examined the association between dietary insulin load (DIL) and insulin index (DII) with developing gestational diabetes mellitus (GDM) during pregnancy. This study aimed to investigate the association between DIL and DII and risk of GDM in a group of pregnant women in Iran. In this prospective cohort study, 812 pregnant in their first trimester were recruited and followed.
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