Cover Image

An Interpretable Machine Learning Approach to Predict Sensory Processing Sensitivity Trait in Nursing Students

Sensory processing sensitivity (SPS) is a personality trait that makes certain individuals excessively sensitive to stimuli. People carrying this trait are defined as Highly Sensitive People (HSP). The SPS trait is notably prevalent among nursing students and nurse staff. Although there are HSP diag...

Full description

Saved in:

Bibliographic Details
Main Authors:	Alicia Ponce-Valencia (Author), Diana Jiménez-Rodríguez (Author), Juan José Hernández Morante (Author), Carlos Martínez Cortés (Author), Horacio Pérez-Sánchez (Author), Paloma Echevarría Pérez (Author)
Format:	Book
Published:	MDPI AG, 2024-04-01T00:00:00Z.
Subjects:	article
Online Access:	Connect to this object online.
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sensory Processing and Autistic Traits: Mediation Effect of Frontal Alpha Asymmetry
by: Deukgeun Yoon, et al.
Published: (2023)

Is sensory processing sensitivity associated with psychoactive substance use?
by: Murielle Mary-Krause, et al.
Published: (2022)

The Impact of Weighted Blanket Use on Adults with Sensory Sensitivity and Insomnia
by: Rhonda Davis-Cheshire, et al.
Published: (2023)

Machine learning for tumor growth inhibition: Interpretable predictive models for transparency and reproducibility
by: Andreas D. Meid, et al.
Published: (2022)

Interpretable Machine Learning Model for Predicting the Prognosis of Guillain-Barré Syndrome Patients
by: Guo J, et al.
Published: (2024)

A review of the impact of sensory processing sensitivity on mental health in university students
by: Allison Mac, PharmD, BCPS, et al.
Published: (2024)

Interpretable Machine Learning Prediction of Drug-Induced QT Prolongation: Electronic Health Record Analysis
by: Steven T Simon, et al.
Published: (2022)

Predicting Leukoplakia and Oral Squamous Cell Carcinoma Using Interpretable Machine Learning: A Retrospective Analysis
by: Salem Shamsul Alam, et al.
Published: (2024)

Prediction and Chemical Interpretation of Singlet-Oxygen-Scavenging Activity of Small Molecule Compounds by Using Machine Learning
by: Taiki Fujimoto, et al.
Published: (2021)

A Systematic Review of Treatment for Children with Autism Spectrum Disorder: The Sensory Processing and Sensory Integration Approach
by: Jonathan Camino-Alarcón, et al.
Published: (2024)

LA IMPORTANCIA DE LA INVESTIGACIÓN EN LOS LENGUAJES ENFERMEROS
by: Paloma Echevarria Pérez
Published: (2013)

Identification of endoplasmic reticulum stress-associated genes and subtypes for prediction of Alzheimer's disease based on interpretable machine learning
by: Yongxing Lai, et al.
Published: (2022)

Construction and validation of predictive models for intravenous immunoglobulin-resistant Kawasaki disease using an interpretable machine learning approach
by: Linfan Deng, et al.
Published: (2024)

Prediction of Online Psychological Help-Seeking Behavior During the COVID-19 Pandemic: An Interpretable Machine Learning Method
by: Hui Liu, et al.
Published: (2022)

Identification of Mitophagy-Associated Genes for the Prediction of Metabolic Dysfunction-Associated Steatohepatitis Based on Interpretable Machine Learning Models
by: Deng B, et al.
Published: (2024)

The lived experience of parenting a child with sensory sensitivity and picky eating
by: Louise Cunliffe, et al.
Published: (2022)

Effect of ageing time in vacuum package on veal longissimus dorsi and biceps femoris physical and sensory traits
by: G. Baldi, et al.
Published: (2015)

Investigating the interactive role of stressful life events, reinforcement sensitivity and personality traits in prediction of the severity of Multiple Sclerosis (MS) symptoms
Published: (2017)

The Impact of Personality Traits and Intercultural Sensitivities of Nursing Students on Their Professional Values
by: Dijle Ayar, et al.
Published: (2019)

Predicting the Skin Sensitization Potential of Small Molecules with Machine Learning Models Trained on Biologically Meaningful Descriptors
by: Anke Wilm, et al.
Published: (2021)

Reduction of monoclonal antibody viscosity using interpretable machine learning
by: Emily K. Makowski, et al.
Published: (2024)

Convergent Validity of Two Sensory Questionnaires in Spain: Sensory Profile-2 and Sensory Processing Measure
by: Berta Gándara-Gafo, et al.
Published: (2023)

Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model
by: Sangmi Kim, et al.
Published: (2024)

Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study
by: Jili Li, et al.
Published: (2022)

Assessing Students' Interpretations of Histograms Before and After Interpreting Dotplots: A Gaze-Based Machine Learning Analysis
by: Lonneke Boels, et al.
Published: (2023)

The role of personality traits in predicting dental anxiety
by: Rahim Yousefi, et al.
Published: (2020)

A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning
by: Bo Zhao, et al.
Published: (2023)

The sensitivity of murine spermiogenesis to miglustat is a quantitative trait: a pharmacogenetic study
by: Boomkamp Stephanie, et al.
Published: (2007)

Nicotine, auditory sensory memory and attention in a human ketamine model of schizophrenia: moderating influence of a hallucinatory trait
by: Verner eKnott, et al.
Published: (2012)

Twenty-eight-day in-hospital mortality prediction for elderly patients with ischemic stroke in the intensive care unit: Interpretable machine learning models
by: Jian Huang, et al.
Published: (2023)

Diagnosis prediction of tumours of unknown origin using ImmunoGenius, a machine learning-based expert system for immunohistochemistry profile interpretation
by: Yosep Chong, et al.
Published: (2021)

Regions of the brain involved with the interpretation of the pain
by: Andrés Orestes Pérez Ruíz, et al.
Published: (2018)

An interpretable machine-learning model for predicting the efficacy of nonsteroidal anti-inflammatory drugs for closing hemodynamically significant patent ductus arteriosus in preterm infants
by: Tai-Xiang Liu, et al.
Published: (2023)

Human Induced Pluripotent Stem Cell Derived Sensory Neurons are Sensitive to the Neurotoxic Effects of Paclitaxel
by: Chenling Xiong, et al.
Published: (2021)

Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches
by: Gabriela Falcón-Cano, et al.
Published: (2022)

Chapter Prediction of wine sensorial quality: a classification problem
by: Carpita, Maurizio
Published: (2021)

Chapter Prediction of wine sensorial quality: a classification problem
by: Carpita, Maurizio
Published: (2021)

Using machine learning to predict antibiotic resistance to support optimal empiric treatment of urinary tract infections
by: Ben Brintz, et al.
Published: (2022)

The Relationship between Children's Trait Emotional Intelligence and the Big Five, Big Two and Big One Personality Traits
by: Èlia López-Cassà, et al.
Published: (2022)

Prediction of Behavioral Problems Based on Attachment Styles and Sensory Processing in Children with a History of Prematurity at Birth
by: Parvin Dibajnia, et al.
Published: (2024)