Use of Classification Algorithms in Health Care

Khan, Hera; Srivastav, Ayush; Mishra, Amit Kumar

doi:10.1108/978-1-83909-099-820201007

Cited by 12 publications

(5 citation statements)

References 18 publications

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“…In practice, it is important to know that the patient treatment quality has several different factors, and the taxonomy of medical, social, and economic factors could be found in the related literature. One critical, systematic review of the existing literature on the application of classification modeling methods related to the general medical application was conducted by Khan et al in [42]. The application of classification modeling methods related to the prediction of the length of hospital stay was considered by Zikos et al [43], as well as in Zikos's doctoral thesis [44].…”

Section: Literature Review Of Different Methodologies That Deal With ...mentioning

confidence: 99%

An Asymmetric Ensemble Method for Determining the Importance of Individual Factors of a Univariate Problem

Mišić,

Kemiveš,

Ranđelović

et al. 2023

Symmetry

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This study proposes an innovative model that determines the importance of selected factors of a univariate problem. The proposed model has been developed based on the example of determining the impact of non-medical factors on the quality of inpatient treatment, but it is generally applicable to any process of binary classification. In addition, an ensemble stacking model that involves the asymmetric use of two different well-known algorithms is proposed to determine the importance of individual factors. This model is constructed so that the standard logistic regression is first applied as mandatory. Further, the classification algorithms are implemented if the defined conditions are met. Finally, feature selection algorithms, which belong to the optimization group of algorithms, are applied as a combinatorial algorithm. The proposed model is verified through a case study conducted using real data obtained from health institutions in the region connected to the city of Nis, Republic of Serbia. The obtained results show that the proposed model can achieve better results than each of the methods included in it and surpasses several state-of-the-art ensemble algorithms in the field of machine learning. The proposed solution has been implemented in the form of a modern mobile application.

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Section: Literature Review Of Different Methodologies That Deal With ...mentioning

confidence: 99%

An Asymmetric Ensemble Method for Determining the Importance of Individual Factors of a Univariate Problem

Mišić,

Kemiveš,

Ranđelović

et al. 2023

Symmetry

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show abstract

“…Educators ______________________________________________________________________________ and students are free to choose the platform for brand engagement in social media. The platform is also found to be used for study purposes [44]. Facebook is a networking site, based on networking, collaboration, and "people's engagement".…”

Section: 2student Brand Engagement As Co-creatorsmentioning

confidence: 99%

Connect with Student-Educational Consumer Brand Management Engagement: A Social Media Management Perspective

Mishra

Negi

Döngül

et al. 2023

AIA

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Social media empowers individuals to express their views regarding the events that take place in their day-to-day life. These events also incorporate the sentiments of students as well as educators towards their educational institutions. Thus, the study aims to analyze the sentiments of the students regarding their educational institutions to hike consumer brand management. However, Understanding the student at all levels of his being (physical, mental, emotional spiritual) is crucial to generate valuable learning and bringing forth a sense of belongingness. The study proposes to use social media platforms to connect, understand and engage the students at the professional as well as personal levels.Design/methodology/approach: Sentiment Analysis using vectorization and polarity has been applied to data collected from tweets of several leading universities of the world with their social media appearances to acquire significant insights into the objective of the study. During the analysis, it has been observed that symbol such as #hashtags and @ has played an intensified role in arousing the emotions of the individuals which eventually contributed to the branding of a particular designated university.Findings: Sentiment and emotional identification play a significant role in increasing brand value and nurturing the relationship between the student and the educator. It has been observed from the study that a sense of intensified community building is promoted which encourages new individuals to become a part of the reputed universities.Research Limitation/Implication: Since the field of education plays a great important role in the policies and economy of every country, students are the driving factors of this sector. Hence it is important to identify the emotion and sentiments of an individual regarding each small role that he goes through while studying. The university plays a very important role thus the study focuses on how each activity in the university affects the sentiments of a student and at the same time, it

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“…To assess the simulated-to-real generalisation, cross-environment tests are applied, and the best correlation coefcient is determined to be 53.96% [16]. Mathematics of SVM, tree-based classifers, and neural networks will go into great detail about ensemble algorithms with appropriate applications [17]. A deep cascaded convolutional neural network (DCNN) has been created to recognise face area and it overcomes the problem in low accuracy using an artifcial feature extraction.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Approach of Face Detection and Prediction of Drowsiness Using SVM

Shukla

Tiwari²,

Jha

2023

Mathematical Problems in Engineering

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This article investigates an issue of road safety and a method for detecting drowsiness in images. More fatal accidents may be averted if fatigued drivers are using this technology accurately and the proposed models provide quick response by recognising the driver’s state of falling asleep. There are the following drowsiness models for depicting the possible eye state classifications as VGG16, VGG19, RESNET50, RESNET101 and MobileNetV2. The absence of a readily available and trustworthy eye dataset is perceived acutely in the realm of eye closure detection. On extracting the deep features of faces with VGG16, 98.68% accuracy has been achieved, VGG19 provides an accuracy of 98.74%, ResNet50 works with 65.69% accuracy, ResNet101 has achieved 95.77%, and MobileNetV2 is achieving 96.00% accuracy with the proposed dataset. The put forth model using the support vector machine (SVM) has been used to evaluate several models, and the present results in terms of loss function and accuracy have been obtained. In the proposed dataset, 99.85% accuracy in detecting facial expressions has been achieved. These experimental results show that the eye closure estimation has a higher accuracy and cheap processing cost, as well as the ability of the proposed framework for drowsiness.

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Use of Classification Algorithms in Health Care

Cited by 12 publications

References 18 publications

An Asymmetric Ensemble Method for Determining the Importance of Individual Factors of a Univariate Problem

An Asymmetric Ensemble Method for Determining the Importance of Individual Factors of a Univariate Problem

Connect with Student-Educational Consumer Brand Management Engagement: A Social Media Management Perspective

An Efficient Approach of Face Detection and Prediction of Drowsiness Using SVM

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