Mahalanobis–Taguchi System to Identify Preindicators of Delirium in the ICU

Buenviaje, Bernardo; Bischoff, John; Roncace, Robert A.; Willy, Christopher J.

doi:10.1109/jbhi.2015.2434949

Cited by 15 publications

(12 citation statements)

References 16 publications

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“…The proposed method estimates the image quality based on MTS and subjective evaluation experiments using the method of successive categories for images evaluation where parameters are combinations of gamma as well as high and minimal luminance Facial identification and/or image Buenviaje et al (2015) Case study The MTS applied to the delirium-evidence-based bundle could detect medical patterns in retrospective data sets. The implication of this paper to a biomedical research is an automated decision support tool for the delirium-evidence-based bundle providing an early detection capability needed today…”

Section: Mts Area Short Description and Resultsmentioning

confidence: 99%

Mahalanobis-Taguchi system: state of the art

Mota-Gutiérrez

Reséndiz‐Flores

Reyes-Carlos

2018

IJQRM

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Purpose The purpose of this paper is to show a bibliographical review of the applications of the MTS throughout the time and the different fields. Design/methodology/approach The Mahalanobis-Taguchi system (MTS) is an analytical method used for the diagnosis and/or pattern recognition of multivariate data for quantitative decision making. Findings Its scope is very broad, ranging from engineering, medicine, education, and manufacturing, among others. This work presents a classification of the literature in the following areas of the MTS: introduction of the method, cases of study/application, comparison with other methods, integration and development of the MTS with other methods, construction of Mahalanobis space, dimensional reduction and threshold establishment. It realized a wide search of the publications in magazines and congresses. Originality/value This paper is a summary of the main applications, contributions and changes to MTS.

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Section: Mts Area Short Description and Resultsmentioning

confidence: 99%

Mahalanobis-Taguchi system: state of the art

Mota-Gutiérrez

Reséndiz‐Flores

Reyes-Carlos

2018

IJQRM

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“…Scholars are becoming gradually more familiar with MTS and constantly try to explore its application or its combination with other theories in different fields. Buenviaje et al [23] obtained medical patterns from historical data sets through MTS. Huang et al [24] utilized the data mining function of MTS, combined it with the artificial neural network (ANN) and came up with the MTS-ANN algorithm.…”

Section: Gemmentioning

confidence: 99%

“…Based on the signal-to-noise ratio and the improved degree of balance and approach, the decision matrix Y is constructed as shown in Equation (23), in which the benefit indicator is η −i and γ +i , while the cost indicator is η +i and γ −i :…”

Section: Scheme Decision-makingmentioning

confidence: 99%

Multi-Dimensional Interval Number Decision Model Based on Mahalanobis-Taguchi System with Grey Entropy Method and Its Application in Reservoir Operation Scheme Selection

Liang

Yang

et al. 2020

Water

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In decision-making with interval numbers, there are problems such as how to reduce the loss of decision information to improve decision accuracy and the difficulty of using interval numbers for sorting. On the basis of fully considering the subjective and objective weights of indexes, the grey entropy method (GEM) is improved by taking advantage of the Mahalanobis-Taguchi System (MTS) in which the orthogonal design has few tests but much obtained information, and the Mahalanobis distance can reflect the correlation between indexes. Then, the signal-to-noise ratio is integrated with the improved degree of balance and approach, and a multi-dimensional interval number decision model based on MTS and GEM is put forth. This model is applied to selecting the optimal scheme of controlling the Pankou reservoir’s water level in flood season. Compared with the decision results of other methods, the optimal scheme selected by the proposed model can achieve greater benefits within an acceptable risk range and thus better coordinate the balance between risk and benefit, which verifies the feasibility and validity of the model.

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“…Therefore, the MS is certainly validated. Hence, Taguchi strategies were used to study the impact of every feature [43,52,53]. The 'Gain' of every feature was computed between these two conditions.…”

Section: Aclr Classificationmentioning

confidence: 99%

Gait Classification Using Mahalanobis–Taguchi System for Health Monitoring Systems Following Anterior Cruciate Ligament Reconstruction

2019

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In this paper, a gait patterns classification system is proposed, which is based on Mahalanobis–Taguchi System (MTS). The classification of gait patterns is necessary in order to ascertain the rehab outcome among anterior cruciate ligament reconstruction (ACLR) patients. (1) Background: One of the most critical discussion about when ACLR patients should return to work (RTW). The objective was to use Mahalanobis distance (MD) to classify between the gait patterns of the control and ACLR groups, while the Taguchi Method (TM) was employed to choose the useful features. Moreover, MD was also utilised to ascertain whether the ACLR group approaching RTW. The combination of these two methods is called as Mahalanobis-Taguchi System (MTS). (2) Methods: This study compared the gait of 15 control subjects to a group of 10 subjects with laboratory. Later, the data were analysed using MTS. The analysis was based on 11 spatiotemporal parameters. (3) Results: The results showed that gait deviations can be identified successfully, while the ACLR can be classified with higher precision by MTS. The MDs of the healthy group ranged from 0.560 to 1.180, while the MDs of the ACLR group ranged from 2.308 to 1509.811. Out of the 11 spatiotemporal parameters analysed, only eight parameters were considered as useful features. (4) Conclusions: These results indicate that MTS can effectively detect the ACLR recovery progress with reduced number of useful features. MTS enabled doctors or physiotherapists to provide a clinical assessment of their patients with more objective way.

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Mahalanobis–Taguchi System to Identify Preindicators of Delirium in the ICU

Cited by 15 publications

References 16 publications

Mahalanobis-Taguchi system: state of the art

Mahalanobis-Taguchi system: state of the art

Multi-Dimensional Interval Number Decision Model Based on Mahalanobis-Taguchi System with Grey Entropy Method and Its Application in Reservoir Operation Scheme Selection

Gait Classification Using Mahalanobis–Taguchi System for Health Monitoring Systems Following Anterior Cruciate Ligament Reconstruction

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