The Kullback-Leibler Divergence Used in Machine Learning Algorithms for Health Care Applications and Hypertension Prediction: A Literature Review

Clim, Antonio; Zota, Răzvan Daniel; Tinică, Grigore

doi:10.1016/j.procs.2018.10.144

Cited by 22 publications

(12 citation statements)

References 12 publications

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“…It is also called relative entropy 28 and is commonly used in machine learning. 29 Intuitively, it quantifies how well one can distinguish between two given distributions by summing over the scaled ratio between two corresponding elements of the two distributions. KLD is an aggregated, order-independent measure.…”

Section: Methodsmentioning

confidence: 99%

Across atoms to crossing continents: application of similarity measures to biological location data

Schuhmann

Ryvkin

McLaren

et al. 2022

Preprint

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Biological processes involve movements across all measurable scales. Similarity measures can be applied to compare and analyze these movements but differ in how differences in movement are aggregated across space and time. The present study reviews frequently-used similarity measures, such as the Hausdorff distance, Frechet distance, Dynamic Time Warping, and Longest Common Subsequence, jointly with several measures less used in biological applications (Wasserstein distance, weak Frechet distance, and Kullback-Leibler divergence), and provides computational tools for each of them that may be used in computational biology. We illustrate the use of the selected similarity measures in diagnosing differences within two extremely contrasting sets of biological data, which, remarkably, may both be relevant for magnetic field perception by migratory birds. Specifically, we assess and discuss cryptochrome protein conformational dynamics and extreme migratory trajectories of songbirds between Alaska and Africa. We highlight how similarity measures contrast regarding computational complexity and discuss those which can be useful in noise elimination or, conversely, are sensitive to spatiotemporal scales.

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Section: Methodsmentioning

confidence: 99%

Across atoms to crossing continents: application of similarity measures to biological location data

Schuhmann

Ryvkin

McLaren

et al. 2022

Preprint

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“…To select the optimal operation environment for this study, the best-performing hyperparameters were chosen using an iterative cross-validation hyperband random search process ( Jiang & Chen 2016;Li et al 2018). In three attempts, the root-mean-square error (RMSE), valorization accuracy (Val-Acc) and Kullback-Leibler divergence (KLD) (Clim et al 2018) were utilized as statistical guidance for the iterative optimization process. The promising median absolute deviation (MAD) was not used due to technical limitations (Gorard 2013; Landwehr et al 2020).…”

Section: Applied Gru Network and Its Hyperparametersmentioning

confidence: 99%

Demonstration of the impacts of anti-sedimentation techniques on Japanese reservoir siltation via mass data ANN analysis

Landwehr

Kantoush

Nohara

et al. 2022

Journal of Hydroinformatics

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Reservoirs have been installed as long-term assets to guarantee water and energy security for decades, if not centuries. However, the effect of siltation undermines reservoirs' sustainability because it significantly reduces the reservoirs' original capacity. Extreme events such as typhoons, floods and droughts are posited to have extreme impacts on sediment inflow and deposition in reservoirs. The same holds true for ISMTs (implemented sediment management technologies), such as dredging, spilling and bypassing. However, the large-scale analysis of their effects on reservoir sedimentation progression, recovery and development was not feasible due to data scarcity and technological restrictions. The present paper closes this information gap by conducting a GRU (gated recurrent unit) neural network analysis of 1,224 Japanese reservoirs, for which the sedimentation, local precipitation, extreme events and ISMTs were monitored between 2000 and 2017. The network reveals the beneficial impacts of dredging, spilling and bypassing. The results also demonstrate the potential of smart management and improved monitoring for sedimentation threat abatement. Thus, foresighted engineering and dedicated governance action in flood and drought scenarios can significantly strengthen the sustainable behavior of key infrastructure elements such as reservoirs.

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“…One measuring tool to evaluate this changing scenario is investments made by venture capitalist in health-care startups (Garbuio and Lin, 2019). Typically, the following key factors determine the growth and sustainability of health care: integrated digital healthcare portfolio inclusive of drugs design, production and its supply chain (Bardy, 2019; Velthoven et al , 2019), health information technology and services and medical devices and sensors (Hogaboam and Daim, 2018); customer data management (including patient digital record keeping, its management and coordination) (Pramanik et al , 2019); digital healthcare data integration (across digital devices and social media, Web data, market data and interhospital) (Saheb and Izadi, 2019); and analytics and big data (Clim et al , 2018; Khennou et al , 2018; Saheb and Izadi, 2019). …”

Section: Literature Reviewmentioning

confidence: 99%

“…2.4.15 Lack of data privacy and security. Data privacy is one of the major concerns in the health-care industry that need to be minimized by BC-T (Clim et al, 2018;Shamshad et al, 2020).…”

Section: Lack Of Technical Expertise To Handle High Complexity Of the Technologymentioning

confidence: 99%

Barriers to blockchain adoption in health-care industry: an Indian perspective

Sharma

Joshi

2021

JGOSS

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Purpose This paper aims to identify barriers toward the adoption of blockchain (BC) technology in Indian health-care industry and also examines the significant issues of BC applications in health-care industry. Design/methodology/approach The barriers of the study are identified by two phases including the review of literature and semistructured interviews with hospital staff and administration operating in India. The experts (N = 15) are being taken from top-level management, IT experts and patients from the hospitals. The study implemented integrated total interpretative structural modeling-FUZZY-Cross-impact matrix multiplication applied to classification (TISM-FUZZY-MICMAC) methods for identifying the interrelationship among the barriers. Findings A total of 15 barriers have been determined in the Indian health-care industry through discussion with the selected experts. TISM is applied to develop multilevel structure for BC barriers. Further, FUZZY-MICMAC has been used to compute driving and dependent barriers. The findings suggest that low awareness related to legal issues and low support from high level of management have maximum driving power. Research limitations/implications The present study applies multicriterion approach to identify the limited barriers in BC adoption in health care. Future studies may develop the relationship and mark down the steps for implementation of BC in health-care setting of a developing economy. Empirical study can be conducted to verify the results along with selected case studies. Practical implications The present study identifies the BC adoption barriers in health-care industry. The study examines the pertinent issues in context to major support required, bottlenecks in adoption, key benefits of adoption planning and activities. The technology adoption practices are expected to provide applications such as distributed, secured medical and clinical data and patient centric systems that will enhance the efficiency of the health-care industry. Originality/value The study is among few primary studies that identify and analyze the BC adoption in health-care industry.

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The Kullback-Leibler Divergence Used in Machine Learning Algorithms for Health Care Applications and Hypertension Prediction: A Literature Review

Cited by 22 publications

References 12 publications

Across atoms to crossing continents: application of similarity measures to biological location data

Across atoms to crossing continents: application of similarity measures to biological location data

Demonstration of the impacts of anti-sedimentation techniques on Japanese reservoir siltation via mass data ANN analysis

Barriers to blockchain adoption in health-care industry: an Indian perspective

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