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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".

Deadline for manuscript submissions: closed (24 October 2023) | Viewed by 5776

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Special Issue Editors

Dr. Leslie Pendrill

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Guest Editor

Department of Measurement Science and Technology, Research Institutes of Sweden (RISE), AWL Sven Hultins Plats 5, vån 4, 412 58 Göteborg, Sweden
Interests: information; task difficulty; person ability; quality assurance; uncertainty; traceability; metrology; measurement system analysis; Rasch

Dr. Jeanette Melin

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Guest Editor

Department of Measurement Science and Technology, Research Institutes of Sweden (RISE), AWL Sven Hultins Plats 5, vån 4, 412 58 Göteborg, Sweden
Interests: measurement science; construct specification equation; human-based measurements; memory measurements; rehabilitation

Dr. Kyle Perkins

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Guest Editor

Retired Professor, School of Education and Human Development, Florida International University, 11200 SW 8th Street, Miami, FL 33199, USA
Interests: developmental dyslexia; Rasch measurement; language testing; second language acquisition

Special Issue Information

Dear Colleagues,

Entropy is simply and generally described as a measure of order related to the amount of “useful” information or “useful” energy. Entropy was first recognized in thermodynamics and has become a central concept in the field of information theory, but there is a further growing interest in other disciplines and across disciplines.

Entropy can be broadly applied in healthcare. For example, the entropy concept can help to model human physiology as well as explain information processing when measuring the cognitive ability of a patient performing a task of a certain level of difficulty. Entropy also finds application when handling information exchange and communication throughout healthcare, ranging from the setting of performance measures for diagnoses to optimizing the organization of queuing. Recent research, including entropy-related tools such as item response theory, psychometrics, and construct specification equations, promises to modernize classic and traditional approaches to make healthcare more efficient, effective, and with better quality.

Therefore, in this Special Issue, we aim to collect a series of papers addressing the applications of entropy in healthcare. Authors with original papers and comprehensive reviews addressing different perspectives of entropy in healthcare are invited.

Dr. Leslie Pendrill
Dr. Jeanette Melin
Dr. Kyle Perkins
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

information
healthcare
metrology
measurement system analysis
measurement science
construct specification equation
human-based measurements
quality assurance
uncertainty
traceability

Published Papers (4 papers)

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27 pages, 2285 KiB

Open AccessArticle

Information from Noise: Measuring Dyslexia Risk Using Rasch-like Matrix Factorization with a Procedure for Equating Instruments

by Mark H. Moulton and Brock L. Eide

Entropy 2023, 25(12), 1580; https://doi.org/10.3390/e25121580 - 24 Nov 2023

Viewed by 1158

Abstract

This study examines the psychometric properties of a screening protocol for dyslexia and demonstrates a special form of matrix factorization called Nous based on the Alternating Least Squares algorithm. Dyslexia presents an intrinsically multidimensional complex of cognitive loads. By building and enforcing a common 6-dimensional space, Nous extracts a multidimensional signal for each person and item from test data that increases the Shannon entropy of the dataset while at the same time being constrained to meet the special objectivity requirements of the Rasch model. The resulting Dyslexia Risk Scale (DRS) yields linear equal-interval measures that are comparable regardless of the subset of items taken by the examinee. Each measure and cell estimate is accompanied by an efficiently calculated standard error. By incorporating examinee age into the calibration process, the DRS can be generalized to all age groups to allow the tracking of individual dyslexia risk over time. The methodology was implemented using a 2019 calibration sample of 828 persons aged 7 to 82 with varying degrees of dyslexia risk. The analysis yielded high reliability (0.95) and excellent receiver operating characteristics (AUC = 0.96). The analysis is accompanied by a discussion of the information-theoretic properties of matrix factorization. Full article

(This article belongs to the Special Issue Applications of Entropy in Health Care)

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13 pages, 327 KiB

Open AccessArticle

Exploring a New Application of Construct Specification Equations (CSEs) and Entropy: A Pilot Study with Balance Measurements

by Jeanette Melin, Helena Fridberg, Eva Ekvall Hansson, Daniel Smedberg and Leslie Pendrill

Entropy 2023, 25(6), 940; https://doi.org/10.3390/e25060940 - 15 Jun 2023

Cited by 1 | Viewed by 910

Abstract

Both construct specification equations (CSEs) and entropy can be used to provide a specific, causal, and rigorously mathematical conceptualization of item attributes in order to provide fit-for-purpose measurements of person abilities. This has been previously demonstrated for memory measurements. It can also be reasonably expected to be applicable to other kinds of measures of human abilities and task difficulty in health care, but further exploration is needed about how to incorporate qualitative explanatory variables in the CSE formulation. In this paper we report two case studies exploring the possibilities of advancing CSE and entropy to include human functional balance measurements. In case study I, physiotherapists have formulated a CSE for balance task difficulty by principal component regression of empirical balance task difficulty values from Berg’s Balance Scale transformed using the Rasch model. In case study II, four balance tasks of increasing difficulty due to diminishing bases of support and vision were briefly investigated in relation to entropy as a measure of the amount of information and order as well as physical thermodynamics. The pilot study has explored both methodological and conceptual possibilities and concerns to be considered in further work. The results should not be considered as fully comprehensive or absolute, but rather open up for further discussion and investigations to advance measurements of person balance ability in clinical practice, research, and trials. Full article

(This article belongs to the Special Issue Applications of Entropy in Health Care)

12 pages, 325 KiB

Open AccessFeature PaperArticle

Forward and Backward Recalling Sequences in Spatial and Verbal Memory Tasks: What Do We Measure?

by Jeanette Melin, Laura Göschel, Peter Hagell, Albert Westergren, Agnes Flöel and Leslie Pendrill

Entropy 2023, 25(5), 813; https://doi.org/10.3390/e25050813 - 18 May 2023

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Abstract

There are different views in the literature about the number and inter-relationships of cognitive domains (such as memory and executive function) and a lack of understanding of the cognitive processes underlying these domains. In previous publications, we demonstrated a methodology for formulating and testing cognitive constructs for visuo-spatial and verbal recall tasks, particularly for working memory task difficulty where entropy is found to play a major role. In the present paper, we applied those insights to a new set of such memory tasks, namely, backward recalling block tapping and digit sequences. Once again, we saw clear and strong entropy-based construct specification equations (CSEs) for task difficulty. In fact, the entropy contributions in the CSEs for the different tasks were of similar magnitudes (within the measurement uncertainties), which may indicate a shared factor in what is being measured with both forward and backward sequences, as well as visuo-spatial and verbal memory recalling tasks more generally. On the other hand, the analyses of dimensionality and the larger measurement uncertainties in the CSEs for the backward sequences suggest that caution is needed when attempting to unify a single unidimensional construct based on forward and backward sequences with visuo-spatial and verbal memory tasks. Full article

(This article belongs to the Special Issue Applications of Entropy in Health Care)

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13 pages, 5967 KiB

Open AccessOpinion

Medical Applications of Nonadditive Entropies

by Constantino Tsallis and Roman Pasechnik

Entropy 2023, 25(4), 578; https://doi.org/10.3390/e25040578 - 28 Mar 2023

Viewed by 1020

Abstract

The Boltzmann–Gibbs additive entropy

S_{B G} = - k \sum_{i} p_{i} ln p_{i}

and associated statistical mechanics were generalized in 1988 into nonadditive entropy

S_{q} = k \frac{1 - \sum_{i} p_{i}^{q}}{q - 1}

and [...] Read more.

The Boltzmann–Gibbs additive entropy

S_{B G} = - k \sum_{i} p_{i} ln p_{i}

and associated statistical mechanics were generalized in 1988 into nonadditive entropy

S_{q} = k \frac{1 - \sum_{i} p_{i}^{q}}{q - 1}

and nonextensive statistical mechanics, respectively. Since then, a plethora of medical applications have emerged. In the present review, we illustrate them by briefly presenting image and signal processings, tissue radiation responses, and modeling of disease kinetics, such as for the COVID-19 pandemic. Full article

(This article belongs to the Special Issue Applications of Entropy in Health Care)

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