Smart HIV/AIDS Digital System Using Big Data Analytics

Ramasamy, V.; Gomathy, B.; Verma, Rishabh

doi:10.1007/978-981-13-0224-4_37

Cited by 3 publications

(4 citation statements)

References 17 publications

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“… No Citation Technique Description 1 56 Network foresight approach To provide an easy and timely data-access interface this research work used networked foresight approach for the prediction of accurate medicine using current and past clinical historical information. This approach provides an easier interface for the patients and doctors to communicate and exchange information regarding their health status 2 8 – 11 , 19 , 57 , 63 , 73 , 78 , 82 , 86 , 92 , 95 , 97 , 111 – 113 , 116 , 120 , 123 – 126 , 128 , 129 , 131 – 133 , 135 , 137 , 139 – 141 , 144 – 147 , 149 – 154 , 156 , 157 Big data analytics for timely data-access purposes These survey papers presents applications of big data analytics in term of facilities like presenting an easier and timely-access mechanism for both patients and practitioners 3 70 , 197 Pig Latin Script programming tool Pig Latin Script is applied to analyse the healthcare datasets against different queries, to enhance health facilities in ...…”

Section: Resultsmentioning

confidence: 99%

“…To address this problem, these research articles propose an IoT-based smart eHelath application that facilitates aged personnel at doorstep 15 7 Intelligent hospital appointment system A smart hospital appointment system was developed in this research article by using the concept of first come-first serve (FIFO) concept. This model not only vanished the concept of traditional doctor-patient appointment system but also helps in fixing the appointment with an expert doctor using healthcare data bank 16 139 Digital HIV/AIDS detection system This research article presents an electronic HIV/AIDS detection system using healthcare big data analytics. Then a regional based monitoring system is developed to monitor these patients.…”

Section: Resultsmentioning

confidence: 99%

“…To provide an easy and timely data-access interface this research work used networked foresight approach for the prediction of accurate medicine using current and past clinical historical information. This approach provides an easier interface for the patients and doctors to communicate and exchange information regarding their health status 2 [8][9][10][11]19,57,63,73,78,82,86,92,95,97,[111][112][113]116,120,[123][124][125][126]128,129,[131][132][133]135,137,[139][140][141][144][145][146][147][149][150][151][152][153][154]156,157 Big data analytics for timely data-access purposes…”

Section: Network Foresight Approachmentioning

confidence: 99%

See 2 more Smart Citations

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Khan

Nazir

2022

Sci Rep

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Big data has revolutionized the world by providing tremendous opportunities for a variety of applications. It contains a gigantic amount of data, especially a plethora of data types that has been significantly useful in diverse research domains. In healthcare domain, the researchers use computational devices to extract enriched relevant information from this data and develop smart applications to solve real-life problems in a timely fashion. Electronic health (eHealth) and mobile health (mHealth) facilities alongwith the availability of new computational models have enabled the doctors and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. Digital transformation of healthcare systems by using of information system, medical technology, handheld and smart wearable devices has posed many challenges to researchers and caretakers in the form of storage, minimizing treatment cost, and processing time (to extract enriched information, and minimize error rates to make optimum decisions). In this research work, the existing literature is analysed and assessed, to identify gaps that result in affecting the overall performance of the available healthcare applications. Also, it aims to suggest enhanced solutions to address these gaps. In this comprehensive systematic research work, the existing literature reported during 2011 to 2021, is thoroughly analysed for identifying the efforts made to facilitate the doctors and practitioners for diagnosing diseases using healthcare big data analytics. A set of rresearch questions are formulated to analyse the relevant articles for identifying the key features and optimum management solutions, and laterally use these analyses to achieve effective outcomes. The results of this systematic mapping conclude that despite of hard efforts made in the domains of healthcare big data analytics, the newer hybrid machine learning based systems and cloud computing-based models should be adapted to reduce treatment cost, simulation time and achieve improved quality of care. This systematic mapping will also result in enhancing the capabilities of doctors, practitioners, researchers, and policymakers to use this study as evidence for future research.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Network Foresight Approachmentioning

confidence: 99%

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Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Khan

Nazir

2022

Sci Rep

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“…With the current overpopulous and technological age, the accessing and processing of fundamental caretakers for the purpose of treatment is a big concern for patients and specifically for the aged patients. e IoT-based applications plays an important role and provide fundamental treatment at the door steps 2019 Journal [86] Smart HIV/AIDS digital system A smart HIV/AIDS digital system is developed by gathering the data from numerous sources regarding the mentioned disease. After this, apply the collected data to an explicit location for monitoring the patients of HIV/AIDS in the explicit region.…”

Section: Reference Technique Descriptionmentioning

confidence: 99%

Parallel Computing for Efficient and Intelligent Industrial Internet of Health Things: An Overview

et al. 2021

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Internet of Things (IoT) is expanding and evolves into all aspects of the society. Research and developments in the field of IoT have shown the possibility of producing huge volume of data and computation among different devices of the IoT. The data collected from IoT devices are transferred to a central server which can further be retrieved and accessed by the service providers for analyzing, processing, and using. Industrial Internet of Health Things (IIoHT) is the expansion of the Internet of Health Things (IoHT) which plays an important role in observing, consulting, monitoring, and treatment process of remote exchange data processes. The linkage of computation and interoperability are supported through various intelligent sensors, controllers, and actuators. The role of parallel computing for efficient and Intelligent Industrial Internet of Health Things is obvious to analyze and process different healthcare situations. A detailed overview of this existing literature is needed through which the research community will provide new solutions for efficient healthcare with the help of IoT based on parallel computing. Therefore, the current study presents a detailed overview of the existing literature for facilitating IIoHT.

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A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming

Nazir

Khan

et al. 2020

IEEE Access

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Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015-2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly. INDEX TERMS Healthcare, big data, big data management, big data analytics.

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Smart HIV/AIDS Digital System Using Big Data Analytics

Cited by 3 publications

References 17 publications

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Systematic analysis of healthcare big data analytics for efficient care and disease diagnosing

Parallel Computing for Efficient and Intelligent Industrial Internet of Health Things: An Overview

A Comprehensive Analysis of Healthcare Big Data Management, Analytics and Scientific Programming

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