Perspectives on Big Data, Cloud-Based Data Analysis and Machine Learning Systems

Big Data and Cognitive Computing, Journal Year: 2023, Volume and Issue: 7(2), P. 104 - 104

Published: May 30, 2023

Huge amounts of digital data are continuously generated and collected from different sources, such as sensors, cameras, in-vehicle infotainment, smart meters, mobile devices, social media platforms, web applications services [...]

Language: Английский

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A descriptive analytics of the COVID-19 pandemic in a middle-income country with forward-looking insights

Healthcare Analytics, Journal Year: 2024, Volume and Issue: 5, P. 100320 - 100320

Published: March 16, 2024

The outbreak of COVID-19 unleashed an unprecedented global pandemic, profoundly impacting lives and economies worldwide. Recognizing its severity, the World Health Organization (WHO) swiftly declared it a public health emergency international concern. In response to this crisis, collaborative efforts have been underway control disease minimize socio-economic impacts epidemic curve holds vital insights into history exposure, transmission, testing, tracing, social distancing measures, community lockdowns, quarantine, isolation, treatment, offering comprehensive perspective on nation's response. One approach gaining crucial is through meticulous analysis available datasets, empowering us effectively inform future strategies responses. This study aims provide descriptive data analytics pandemic in Philippines, summarizing country's fight by visualizing epidemiological mobility revisiting scientific papers news articles, creating timeline critical issues faced during pandemic. By leveraging these multifaceted analyses, policymakers authorities can make informed decisions enhance preparedness, expand inter-agency cooperation, combat crises. seeks serve as valuable resource, guiding nations worldwide comprehending responding challenges posed beyond.

Language: Английский

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Data Security and Legal Issues in the Application of Medical Big Data

Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 311 - 328

Published: June 7, 2024

This chapter systematically explores the challenges of data security and legal issues in application medical big data. As expands from clinical diagnostics to drug development, it holds vast potential for growth. However, numerous regarding ethics also arise. The begins with an overview current state applications introduces their across various fields. It then delves into faced security. In terms law ethics, discusses conflict between ownership sharing, international frameworks, examines related artificial intelligence ethics. Through detailed case studies, this analyzes breach incidents summarizes impact these events common challenges. intention is guide secure lawful use while protecting patient privacy integrity.

Language: Английский

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Artificial intelligence and big data from digital health applications: publication trends and analysis

Journal of Health Organization and Management, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 20, 2024

The integration of big data with artificial intelligence in the field digital health has brought a new dimension to healthcare service delivery. AI technologies that provide value by using obtained provision services are being added each passing day. There also some problems related use In this respect, it is aimed understand health, and analyze developments trends sector.

Language: Английский

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Understanding Medical 4.0 implementation through enablers: An integrated multi-criteria decision-making approach

Informatics and Health, Journal Year: 2023, Volume and Issue: 1(1), P. 29 - 39

Published: Dec. 26, 2023

Integrating advanced digital technologies into healthcare systems, known as the Medical 4.0 paradigm, has brought about a revolutionary transformation in medical field. Thus, to incorporate these systematically and effectively sector, it is imperative prioritise key enabling factors. This strategic approach streamlines resource allocation, risk management, achievement of significant outcomes. In this context, ten crucial enablers play pivotal roles: Policy Support, enhanced diagnostics treatment, patient-centric care, telehealth Telemedicine, Internet Things devices, artificial intelligence, cloud computing, genomics precision medicine, Cybersecurity, industry collaboration. paper introduces delves primary driving transformative process. The importance critical success assessed using fuzzy TOPSIS MARCOS methods, which established quantitative framework for decision-making prioritisation within landscape. A comprehensive set evaluation criteria proposed, encompassing cost-effectiveness, adaptability, mitigation, Data Privacy, interoperability, ease implementation, stakeholder acceptance, environmental impact, supplier partner compatibility, regulatory compliance. research enhances our comprehension dynamics propelling implementation 4.0, providing valuable insights unlock potential technology-driven advancements. By employing quantifiable model guide efforts expansive domain. results are further validated through sensitivity analysis. offers invaluable both professionals researchers looking harness possibilities offered by advancements healthcare.

Language: Английский

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Hybrid Encryption Algorithm for Information Security in Hadoop

International Journal of Advanced Computer Science and Applications, Journal Year: 2023, Volume and Issue: 14(6)

Published: Jan. 1, 2023

Network security has gained importance in recent years. Information system is greatly aided by the development of encryption as a solution. To safeguard shared information, several strategies are required. Thanks to cutting-edge Internet, networking corporations, health and cloud applications, our data growing exponentially every minute. In order handle enormous amounts efficiently, new application called Hadoop distributed file (HDFS) was created. However, HDFS doesn't come with any built-in tools, which poses serious risks. increase security, techniques established; nevertheless, standard algorithms fall short when dealing bigger files. this study, huge will be secured using novel hybrid algorithm that combines CP-ABE (encryption based on features policy), AES (advanced encryption), RSA (Rivest-Shamir-Adleman). The suggested model's performance compared against traditional like DES, 3DES, Blowfish demonstrate improved it relates decryption time, throughput. results studies method's more secure.

Language: Английский

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Developing a Smart Healthy City Using Twitter Big Data by Modified Deep Belief Network

Published: Sept. 1, 2023

Big data, which is fueled by IT, opens up fresh avenues for urban renewal. The integration and exchange of as well the optimization rudimentary standards smart cities, are greatly improved application several scientific advances, including (IoT) data collecting analytics. idea underlying key study issue in creation keen educational institutions, industrial establishments, commercial enterprises during last years. services it enables crucial to developing environmentally friendly metropolises. Several studies have evaluated shown that AI most effective method enhancing cities' fire detection effectiveness. In contrast, people cities increasingly turning SNS learn about latest updates on epidemic, discuss with others, report their own experiences it. this study, we offer a framework analysis big from social media platforms like Twitter order predict spread COVID-19 virus Smart Sustainable Healthy City. After over 10,000 Tweets course two months, researchers found 38% users were between ages 18 29, 26% 30 49. About 56% male 44% female. tweets sorted using Natural Language Processing (NLP). For tweet categorization, utilise modified version Deep Belief Network (MDBN), tweaks made weights original network. Election Algorithm responsible carrying out (EA). Based findings, cluster epidemic cases was anticipated seven days before verified cases. indication 0.96. By analysing platforms, able foresee.

Language: Английский

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Utilizing Nlp And Machine Learning To Predict Patient Outcomes From Electronic Health Records In Cloud Environments

Published: Dec. 29, 2023

In stored in the cloud healthcare systems, this research investigates incorporation of machine learning (ML) along with natural language processing (NLP) for statistical analysis employing electronic health records (EHRs). Using a design based on description and additional data collection, our own deductive approach adopts an interpretivist framework. Unstructured medical writing can yield insights that NLP techniques use to inform creation models are predictive. The outcomes demonstrate how well ML perform predicting patient useful is structuring EHR data. study tackles cloud-based setting scalability issues highlights ability interpret by means SHAP values.

Language: Английский

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Dynamic Data Placement Strategy with Network Security Issues in Distributed Cloud Environment for Medical Issues: An Overview

Recent Advances in Computer Science and Communications, Journal Year: 2024, Volume and Issue: 17(6)

Published: Feb. 7, 2024

: The rapid integration of distributed cloud systems in the healthcare industry has profoundly impacted management valuable medical data. While this advancement significantly improved data handling, protecting sensitive information such a complex environment remains daunting. This comprehensive study explores crucial intersection between dynamic placement strategies and network security concerns environments, particularly healthcare. After establishing significance context research, survey delves into growing need to safeguard within everevolving landscape cloud-based systems. It lays out fundamental concepts, as security, highlighting their unique implications domain. Ultimately, sheds light on most effective approaches for balancing sector. research examining many tactics, evaluating effectiveness handling delicate information, presenting tangible use cases. A key focus investigation is fusion organization safety industry. investigates adaptability positioning techniques fortifying safeguarding against potential threats Case studies successful implementation these establishments are also included.

Language: Английский

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Population Health Management: A Bibliometric Analysis of Literature on Data Analytics and Public Health Interventions

West Science Interdisciplinary Studies, Journal Year: 2024, Volume and Issue: 2(04), P. 778 - 788

Published: April 30, 2024

Population health management (PHM) has emerged as a pivotal strategy in healthcare, aiming to address the needs of communities while enhancing care quality and outcomes. Recent years have witnessed surge research at intersection data analytics public interventions within realm PHM. This paper presents comprehensive bibliometric analysis literature on context population management. Through systematic collection from reputable scholarly databases rigorous analysis, this study aims map out trends, key contributors, emerging themes shaping discourse domain. The encompasses publication authorship patterns, citation metrics, network visualizations provide insights into landscape literature. Notable findings include high rate per author, indicative interest collaboration community. Key identified outcomes, interventions, improvement, determinants, disparities. Additionally, temporal reveals shift towards non-communicable diseases increasing role patient care. author highlights core cluster researchers with extensive collaborative ties, alongside peripheral authors topics representing specialized or nascent areas. density visualization identifies potential areas for future research, including disparities, women's issues, geographic-specific studies.

Language: Английский

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