Ontology Driven Smart Health Service Integration

Shahzad, Syed Khuram; Ahmed, Daniyal; Naqvi, Muhammad Raza; Mushtaq, Muhammad Tahir; Iqbal, Muhammad Waseem; Munir, Farrukh

doi:10.1016/j.cmpb.2021.106146

Cited by 34 publications

(18 citation statements)

References 6 publications

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“…This showed 86.89% accuracy, 91.60% sensitivity, and 80.46% specificity. later research, [11] explained first-class originality to describe the irregularity of border of skin lesion images that gets from a standard camera. He proposed irregularity of border HLIFs combined with other features.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Color Texture Features Classification Through ANN for Melanoma

Mustafa¹,

Jaffar²,

Iqbal³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Melanoma is of the lethal and rare types of skin cancer. It is curable at an initial stage and the patient can survive easily. It is very difficult to screen all skin lesion patients due to costly treatment. Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders, pigment networks, and the color of melanoma. These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease. The trained clinicians can overcome the issues such as low contrast, lesions varying in size, color, and the existence of several objects like hair, reflections, air bubbles, and oils on almost all images. Active contour is one of the suitable methods with some drawbacks for the segmentation of irregular shapes. An entropy and morphology-based automated mask selection is proposed for the active contour method. The proposed method can improve the overall segmentation along with the boundary of melanoma images. In this study, features have been extracted to perform the classification on different texture scales like Gray level co-occurrence matrix (GLCM) and Local binary pattern (LBP). When four different moments pull out in six different color spaces like HSV, Lin RGB, YIQ, YCbCr, XYZ, and CIE L*a*b then global information from different colors channels have been combined. Therefore, hybrid fused texture features; such as local, color feature as global, shape features, and Artificial neural network (ANN) as classifiers have been proposed for the categorization of the malignant and non-malignant. Experimentations had been carried out on datasets Dermis, DermQuest, and PH2. The results of our advanced method showed superiority and contrast with the existing state-of-the-art techniques.

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Section: Related Workmentioning

confidence: 99%

Hybrid Color Texture Features Classification Through ANN for Melanoma

Mustafa¹,

Jaffar²,

Iqbal³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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“…The term SOA refers to a networked, standards-based interface architecture that enables the convergence of business processes as a linked service and a roadmap to innovation. In the classical model of SOA [20], there are clearly identified three main actors: service provider, service consumer and registry of services [21].…”

Section: Background and Related Workmentioning

confidence: 99%

“…The behavior of processes, inefficiencies, anomalies and inconsistencies in the processes can be perceived by analysts with the help of BPMN diagrams [28]. Here a few examples from literature are Smart home-procurement process BPMN [20] Smart home temperature sensing and management Unified Modelling Language (UML) [21] Temperature sensors management UML [28] Patient health, appointment, ambulance record BPMN [29] Smart grid BPMN [30] Smart pills box Flow chart [31] Smart medicine box Flow chart [32] Noise level management Flow chart We agree with the authors of [33] to develop mathematical frameworks along with graphical models to explain the main components of smart services, the properties of these components and the relationships between them. According to this approach a smart service 'S' can be represented in the form of relation as in the following Eq.…”

Section: Business Process Modeling and Languagesmentioning

confidence: 99%

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A Process Oriented Integration Model for Smart Health Services

Gondal¹,

Shahzad²,

Jaffar³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Cities are facing challenges of high rise in population number and consequently need to be equipped with latest smart services to provide luxuries of life to its residents. Smart integrated solutions are also a need to deal with the social and environmental challenges, caused by increasing urbanization. Currently, the development of smart services' integrated network, within a city, is facing the barriers including; less efficient collection and sharing of data, along with inadequate collaboration of software and hardware. Aiming to resolve these issues, this paper recommended a solution for a synchronous functionality in the smart services' integration process through modeling technique. Using this integration modeling solution, at first, the service participants, processes and tasks of smart services are identified and then standard illustrations are developed for the better understanding of the integrated service group environment. Business process modeling and notation (BPMN) language based models are developed and discussed for a devised case study, to test and experiment i.e., for remote healthcare from a smart home. The research is concluded with the integration process model application for the required data sharing among different service groups. The outcomes of the modeling are better understanding and attaining maximum automation that can be referenced and replicated.

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“…SWRL (Semantic Web Rule Language) used to express the rules as logic in OWL web ontology language. Pellet reasoner was used to assure the ontology consistency and coherence [30][31][32].…”

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confidence: 99%

A-SHIP: Ontology-Based Adaptive Sustainable Healthcare Insurance Policy

et al. 2022

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Healthcare has a significant impact on human capital anywhere. Countries usually allocate financial resources to manage healthcare, which might impose a substantial financial burden on the scope of healthcare coverage. Thus, the healthcare sector must provide the best possible services at the lowest cost. This significant challenge can only be achieved through applying appropriate policies and technologies, including those used by healthcare insurance policy providers. This paper proposes an innovative, customer-centric, sustainable healthcare insurance policy model. The main objective of this model is to sustain wellness by applying technologies to avoid illness and provide wellbeing for patients by empowering self-care remotely. The proposed solution uses an adaptive ontology-based knowledge management system to satisfy customers and market needs. The proposed system creates a customized policy that consists of various packages to match customers’ healthcare needs based on their health status. The system was tested and validated using a real dataset.

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Ontology Driven Smart Health Service Integration

Cited by 34 publications

References 6 publications

Hybrid Color Texture Features Classification Through ANN for Melanoma

Hybrid Color Texture Features Classification Through ANN for Melanoma

A Process Oriented Integration Model for Smart Health Services

A-SHIP: Ontology-Based Adaptive Sustainable Healthcare Insurance Policy

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