scholarly journals Intelligent Healthcare Systems Assisted by Data Analytics and Mobile Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Xiao Ma ◽  
Zie Wang ◽  
Sheng Zhou ◽  
Haoyu Wen ◽  
Yin Zhang
Keyword(s):  
Mobile Computing ◽  
Data Analytics ◽  
State Of The Art ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Healthcare Applications ◽  
Novel Technologies ◽  
Cognitive Power ◽  
Intelligent Healthcare ◽  
Learning Data

It is entering an era of big data, which facilitated great improvement in various sectors. Particularly, assisted by wireless communications and mobile computing, mobile devices have emerged with a great potential to renovate the healthcare industry. Although the advanced techniques will make it possible to understand what is happening in our body more deeply, it is extremely difficult to handle and process the big health data anytime and anywhere. Therefore, data analytics and mobile computing are significant for the healthcare systems to meet many technical challenges and problems that need to be addressed to realize this potential. Furthermore, the advanced healthcare systems have to be upgraded with new capabilities such as machine learning, data analytics, and cognitive power for providing human with more intelligent and professional healthcare services. To explore recent advances and disseminate state-of-the-art techniques related to data analytics and mobile computing on designing, building, and deploying novel technologies, to enable intelligent healthcare services and applications, this paper presents the detailed design for developing intelligent healthcare systems assisted by data analytics and mobile computing. Moreover, some representative intelligent healthcare applications are discussed to show that data analytics and mobile computing are available to enhance the performance of the healthcare services.

scholarly journals Industry 4.0 Applications for Medical/Healthcare Services

2021 ◽  
Vol 10 (3) ◽  
pp. 43
Author(s):  
Shuva Paul ◽  
Muhtasim Riffat ◽  
Abrar Yasir ◽  
Mir Nusrat Mahim ◽  
Bushra Yasmin Sharnali ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Data Analytics ◽  
Industrial Revolution ◽  
State Of The Art ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Start Ups ◽  
Medical Healthcare

At present, the whole world is transitioning to the fourth industrial revolution, or Industry 4.0, representing the transition to digital, fully automated environments, and cyber-physical systems. Industry 4.0 comprises many different technologies and innovations, which are being implemented in many different sectors. In this review, we focus on the healthcare or medical domain, where healthcare is being revolutionized. The whole ecosystem is moving towards Healthcare 4.0, through the application of Industry 4.0 methodologies. Many technical and innovative approaches have had an impact on moving the sector towards the 4.0 paradigm. We focus on such technologies, including Internet of Things, Big Data Analytics, blockchain, Cloud Computing, and Artificial Intelligence, implemented in Healthcare 4.0. In this review, we analyze and identify how their applications function, the currently available state-of-the-art technologies, solutions to current challenges, and innovative start-ups that have impacted healthcare, with regards to the Industry 4.0 paradigm.

scholarly journals Ontology-based IoT healthcare systems (IHS) for Senior Citizens

2021 ◽  
Vol 6 (2) ◽  
pp. 0-0
Keyword(s):  
Senior Citizens ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
The Internet ◽  
Healthcare Applications ◽  
Smooth Flow ◽  
Incremental Growth ◽  
Current Scenario ◽  
The Impact ◽  
The Internet Of Things

Rapid incremental growth in population causes the virulence of infectious diseases worldwide. Due to this, health hazards with population growth raise pollution in the air, water, and soil and affect the immunity of individuals. To handle the situation, reliable and easy to reach healthcare services are required. The proliferation of connected technologies along with the Internet of Things (IoT) is providing modern healthcare with extensive care. All-pervading IoT technology gaining a very much attraction nowadays. This paper presents a brief about the E-Health Care System along with its framework. This attempt also presents the ontology approach as data produced by healthcare applications is vast and unstructured which needs to be organized in proper format with a smooth flow of data and also results in less request-response time. Further, this paper discusses the impact of the disease on senior citizens in the current scenario.

Big Data, Data Mining, and Data Analytics in IoT-Based Healthcare Applications

2022 ◽  
pp. 1035-1053
Author(s):  
Isakki Alias Devi P
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analytics ◽  
Health Management ◽  
Health Resources ◽  
Healthcare Services ◽  
Data Systems ◽  
Healthcare Applications ◽  
Big Data Systems ◽  
Iot Devices

IoT seriously impacts every industry. The healthcare industry has experienced progression in digitizing medical records. Healthcare services are costlier than ever. Data mining is one of the largest challenges to face IoT. Big Data is an accumulation of data. IoT devices receive lots of data. Big data systems can do a lot of data analytics. The tools can also be used to perform these operations. The big health application system can be built by integrating medical health resources using intelligent terminals, internet of things (IoT), big data, and cloud computing. People suffer from many diseases. A big health system can be applied to scientific health management by detecting risk factors for the occurrence of diseases. Patients can have special attention to their health requirements and their devices can be tuned to remind them of their appointments, calorie count, exercise check, blood pressure variations, symptoms of any diseases, and so much more.

scholarly journals Health-BlockEdge: Blockchain-Edge Framework for Reliable Low-Latency Digital Healthcare Applications

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2502
Author(s):  
Muneeb Ejaz ◽  
Tanesh Kumar ◽  
Ivana Kovacevic ◽  
Mika Ylianttila ◽  
Erkki Harjula
Keyword(s):  
Low Cost ◽  
Effective Means ◽  
Rapid Evolution ◽  
Dynamic Network ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Healthcare Sector ◽  
Elderly Persons ◽  
Healthcare Applications ◽  
Blockchain Technology

The rapid evolution of technology allows the healthcare sector to adopt intelligent, context-aware, secure, and ubiquitous healthcare services. Together with the global trend of an aging population, it has become highly important to propose value-creating, yet cost-efficient digital solutions for healthcare systems. These solutions should provide effective means of healthcare services in both the hospital and home care scenarios. In this paper, we focused on the latter case, where the goal was to provide easy-to-use, reliable, and secure remote monitoring and aid for elderly persons at their home. We proposed a framework to integrate the capabilities of edge computing and blockchain technology to address some of the key requirements of smart remote healthcare systems, such as long operating times, low cost, resilience to network problems, security, and trust in highly dynamic network conditions. In order to assess the feasibility of our approach, we evaluated the performance of our framework in terms of latency, power consumption, network utilization, and computational load, compared to a scenario where no blockchain was used.

Big Data, Data Mining, and Data Analytics in IoT-Based Healthcare Applications

2020 ◽  
pp. 224-242
Author(s):  
Isakki Alias Devi P
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Analytics ◽  
Health Management ◽  
Health Resources ◽  
Healthcare Services ◽  
Data Systems ◽  
Healthcare Applications ◽  
Big Data Systems ◽  
Iot Devices

IoT seriously impacts every industry. The healthcare industry has experienced progression in digitizing medical records. Healthcare services are costlier than ever. Data mining is one of the largest challenges to face IoT. Big Data is an accumulation of data. IoT devices receive lots of data. Big data systems can do a lot of data analytics. The tools can also be used to perform these operations. The big health application system can be built by integrating medical health resources using intelligent terminals, internet of things (IoT), big data, and cloud computing. People suffer from many diseases. A big health system can be applied to scientific health management by detecting risk factors for the occurrence of diseases. Patients can have special attention to their health requirements and their devices can be tuned to remind them of their appointments, calorie count, exercise check, blood pressure variations, symptoms of any diseases, and so much more.

scholarly journals Big Data Analytics for Improved Care Delivery in the Healthcare Industry

2019 ◽  
Vol 15 (10) ◽  
pp. 40
Author(s):  
Gunasekar Thangarasu ◽  
Kayalvizhi Subramanian
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Care Delivery ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Big Data Analysis ◽  
Unstructured Data ◽  
Effective Practices ◽  
Healthcare Industry

<p class="0abstract">The big data analytics plays a pivotal role in the field of healthcare services and research to facilitate better service to the patients. It has provided tools to accumulate, manage, analysis the structured and unstructured data produced by the healthcare systems. Recently the utilization of big data analytics has been increased in the healthcare industry for assisting the process of diagnosing diseases and care delivery. However, the adoption and research development of big data analysis in the healthcare industry is still slow down due to facing some fundamental problems inherent within the big data paradigm. In this study, addresses these problems which focus on the upcoming and promising areas of medical research and proposed a novel big data analytics approach using Apache Spark. The proposed approach will improve care delivery in the healthcare industry. Big data analytics can continually evaluate clinical data in order to improve the effective practices of physicians and improved patient care.</p>

An Optimized Approach for Breast Cancer Classification for Histopathological Images Based on Hybrid Feature Set

2020 ◽  
Vol 16 ◽  
Author(s):  
Inzamam Mashood Nasir ◽  
Muhammad Rashid ◽  
Jamal Hussain Shah ◽  
Muhammad Sharif ◽  
Muhammad Yahiya Haider Awan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
State Of The Art ◽  
Hybrid Approach ◽  
Classification Performance ◽  
Diagnose Breast Cancer ◽  
Histopathological Images ◽  
And Performance ◽  
Learned Features ◽  
Intelligent Healthcare

Background: Breast cancer is considered as the most perilous sickness among females worldwide and the ratio of new cases is expanding yearly. Many researchers have proposed efficient algorithms to diagnose breast cancer at early stages, which have increased the efficiency and performance by utilizing the learned features of gold standard histopathological images. Objective: Most of these systems have either used traditional handcrafted features or deep features which had a lot of noise and redundancy, which ultimately decrease the performance of the system. Methods: A hybrid approach is proposed by fusing and optimizing the properties of handcrafted and deep features to classify the breast cancer images. HOG and LBP features are serially fused with pretrained models VGG19 and InceptionV3. PCR and ICR are used to evaluate the classification performance of proposed method. Results: The method concentrates on histopathological images to classify the breast cancer. The performance is compared with state-of-the-art techniques, where an overall patient-level accuracy of 97.2% and image-level accuracy of 96.7% is recorded. Conclusion: The proposed hybrid method achieves the best performance as compared to previous methods and it can be used for the intelligent healthcare systems and early breast cancer detection.

Novel Technologıes and Nanotoxıcology of Medıcal Implants

2020 ◽  
Vol 16 ◽  
Author(s):  
Ramazan Akçan ◽  
Halit Canberk Aydogan ◽  
Mahmut Şerif Yıldırım ◽  
Burak Taştekin ◽  
Necdet Sağlam
Keyword(s):  
Human Health ◽  
Human Body ◽  
Diagnostic Procedures ◽  
Toxic Effects ◽  
Medical Implants ◽  
Healthcare Applications ◽  
Detailed Review ◽  
Novel Technologies ◽  
Technological Developments

Background/aim: Use of nanomaterials in the healthcare applications increases in parallel to technological developments. It is frequently utilized in diagnostic procedures, medications and in therapeutic implementations. Nanomaterials take place among key components of medical implants, which might be responsible for certain toxic effects on human health at nano-level. In this review, nanotoxicological effects, toxicity determination of nanobiomaterials used in human body and their effects on human health are discussed. Material and Method: A detailed review of related literature was performed and evaluated as per nanomaterials and medical implants. Results and Conclusion: The nanotoxic effects of the materials applied to human body and the determination of its toxicity are important. Determination of toxicity for each nanomaterial requires a detailed and multifactorial assessment considering the properties of these materials. There are limited studies in the literature regarding the toxic effects of nanomaterials used in medical implants. Although these implants are potentially biocompatible and biodegradable, it is highly important to discuss nanotoxicological characteristics of medical implant.

scholarly journals HealthTEC Innovation Design - a proposal for a novel Master degree program based on Unmet Clinical Need, global Healthcare Challenges, and 21st century skills

2020 ◽  
Vol 6 (3) ◽  
pp. 599-603
Author(s):  
Michael Friebe
Keyword(s):  
Machine Learning ◽  
21St Century ◽  
21St Century Skills ◽  
Data Analytics ◽  
Industrial Revolution ◽  
Data Gathering ◽  
Healthcare Systems ◽  
Disruptive Innovation ◽  
Incremental Innovation ◽  
Healthcare Provision

AbstractThe effectiveness, efficiency, availability, agility, and equality of global healthcare systems are in question. The COVID-19 pandemic have further highlighted some of these issues and also shown that healthcare provision is in many parts of the world paternalistic, nimble, and often governed too extensively by revenue and profit motivations. The 4th industrial revolution - the machine learning age - with data gathering, analysis, optimisation, and delivery changes has not yet reached Healthcare / Health provision. We are still treating patients when they are sick rather then to use advanced sensors, data analytics, machine learning, genetic information, and other exponential technologies to prevent people from becoming patients or to help and support a clinicians decision. We are trying to optimise and improve traditional medicine (incremental innovation) rather than to use technologies to find new medical and clinical approaches (disruptive innovation). Education of future stakeholders from the clinical and from the technology side has not been updated to Health 4.0 demands and the needed 21st century skills. This paper presents a novel proposal for a university and innovation lab based interdisciplinary Master education of HealthTEC innovation designers.

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