ArticleEntropy (Basel, Switzerland)2020
Fever Time Series Analysis Using Slope Entropy. Application to Early Unobtrusive Differential Diagnosis.
Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Next generation bioelectronic medicine: making the case for non-invasive closed-loop autonomic neuromodulation.Bioelectronic medicine · 2025Review
- Research on Sea State Signal Recognition Based on Beluga Whale Optimization-Slope Entropy and One Dimensional-Convolutional Neural Network.Sensors (Basel, Switzerland) · 2024Article
- Slope Entropy Characterisation: An Asymmetric Approach to Threshold Parameters Role Analysis.Entropy (Basel, Switzerland) · 2024Article
- A Dual-Optimization Fault Diagnosis Method for Rolling Bearings Based on Hierarchical Slope Entropy and SVM Synergized with Shark Optimization Algorithm.Sensors (Basel, Switzerland) · 2023Article
- Non-Monotonic Complexity of Stochastic Model of the Channel Gating Dynamics.Entropy (Basel, Switzerland) · 2023Article
- Slope Entropy Normalisation by Means of Analytical and Heuristic Reference Values.Entropy (Basel, Switzerland) · 2022Article
- Slope Entropy Characterisation: The Role of theEntropy (Basel, Switzerland) · 2022Article
- Discriminating Bacterial Infection from Other Causes of Fever Using Body Temperature Entropy Analysis.Entropy (Basel, Switzerland) · 2022Article
- A novel method for measuring sublingual temperature using conventional non-contact forehead thermometer.F1000Research · 2022Article
- Double Feature Extraction Method of Ship-Radiated Noise Signal Based on Slope Entropy and Permutation Entropy.Entropy (Basel, Switzerland) · 2021Article
- Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study.Entropy (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Fever is a readily measurable physiological response that has been used in medicine for centuries. However, the information provided has been greatly limited by a plain thresholding approach, overlooking the additional information provided by temporal variations and temperature values below such threshold that are also representative of the subject status. In this paper, we propose to utilize continuous body temperature time series of patients that developed a fever, in order to apply a method capable of diagnosing the specific underlying fever cause only by means of a pattern relative frequency analysis. This analysis was based on a recently proposed measure, Slope Entropy, applied to a variety of records coming from dengue and malaria patients, among other fever diseases. After an input parameter customization, a classification analysis of malaria and dengue records took place, quantified by the Matthews Correlation Coefficient. This classification yielded a high accuracy, with more than 90% of the records correctly labelled in some cases, demonstrating the feasibility of the approach proposed. This approach, after further studies, or combined with more measures such as Sample Entropy, is certainly very promising in becoming an early diagnosis tool based solely on body temperature temporal patterns, which is of great interest in the current Covid-19 pandemic scenario.
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