Need of Technology Changes in Hospital Domains for Improved Nursing Service using Ai (Artificial Intelligence) and IoT (Internet of Things)

Healthcare has come a long way with the technological upgrades that it has witnessed and embraced. Technological disrupters like automation, big data, cloud, AI, IOT, have contributed in making the healthcare domain more enhanced and efficient. In the healthcare when we focus more on hospital related services, we see that the changes have started to reflect. Considering Nursing as one of the major services, this study attempts to understand the long ranging impact of AI and IOT on nursing specifically. Nursing as a choice of work has always been looked down upon by the society. The overall work environments, pay structures have also not been conducive for the work force. Being a crucial component of the healthcare domain, the impact of AI and IOT would be more pronounced and visible on nursing in the coming years. The paper attempts to find the gaps and areas of improvement in nursing to make it more efficient. Research Methods and Approach: The paper finds relevant attributes which impact the performance of the nurses. The attributes are derived using mixed method of research and triangulation. This is planned by conducting the systematic literature review followed first by qualitative research methodology based semi structured interviews of patients and their relatives and later by interviewing the doctors and nurses, hospital management. A Systematic literature review of minimum 75 to 100 research papers from the following databases Pubmed, Ieee, ACM, Science Direct and Google Scholar was planned. For the interviews it was decided to conduct a heterogeneous quota sampling for interviewing the patients, their relatives and doctors and nurses, hospital management. Purpose of the Study: Artificial intelligence and Internet-of-Things are the most path breaking techniques today69. The paper integrates these in the hospital domain focussing only “nursing” as service. It answers the crucial research questions like ‘If AI and IOT is used as a methodology in ”nursing Services” ,visualizing the impact of AI enabled Bots in nursing, pros and cons of introducing the AI technology intervention in Nursing and to conceptualize a model for the same.

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Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review

Electronics ◽

10.3390/electronics11020198 ◽

2022 ◽

Vol 11 (2) ◽

pp. 198

Author(s):

Mujaheed Abdullahi ◽

Yahia Baashar ◽

Hitham Alhussian ◽

Ayed Alwadain ◽

Norshakirah Aziz ◽

...

Keyword(s):

Artificial Intelligence ◽

Neural Networks ◽

Internet Of Things ◽

Literature Review ◽

Systematic Literature Review ◽

Rapid Development ◽

Security And Privacy ◽

Gradient Boosting ◽

Support Vector ◽

Extreme Gradient Boosting

In recent years, technology has advanced to the fourth industrial revolution (Industry 4.0), where the Internet of things (IoTs), fog computing, computer security, and cyberattacks have evolved exponentially on a large scale. The rapid development of IoT devices and networks in various forms generate enormous amounts of data which in turn demand careful authentication and security. Artificial intelligence (AI) is considered one of the most promising methods for addressing cybersecurity threats and providing security. In this study, we present a systematic literature review (SLR) that categorize, map and survey the existing literature on AI methods used to detect cybersecurity attacks in the IoT environment. The scope of this SLR includes an in-depth investigation on most AI trending techniques in cybersecurity and state-of-art solutions. A systematic search was performed on various electronic databases (SCOPUS, Science Direct, IEEE Xplore, Web of Science, ACM, and MDPI). Out of the identified records, 80 studies published between 2016 and 2021 were selected, surveyed and carefully assessed. This review has explored deep learning (DL) and machine learning (ML) techniques used in IoT security, and their effectiveness in detecting attacks. However, several studies have proposed smart intrusion detection systems (IDS) with intelligent architectural frameworks using AI to overcome the existing security and privacy challenges. It is found that support vector machines (SVM) and random forest (RF) are among the most used methods, due to high accuracy detection another reason may be efficient memory. In addition, other methods also provide better performance such as extreme gradient boosting (XGBoost), neural networks (NN) and recurrent neural networks (RNN). This analysis also provides an insight into the AI roadmap to detect threats based on attack categories. Finally, we present recommendations for potential future investigations.

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A Systematic Literature Review About the Impact of Artificial Intelligence on Autonomous Vehicle Safety

IEEE Transactions on Intelligent Transportation Systems ◽

10.1109/tits.2019.2949915 ◽

2020 ◽

Vol 21 (12) ◽

pp. 4928-4946 ◽

Cited By ~ 5

Author(s):

Alexandre Moreira Nascimento ◽

Lucio Flavio Vismari ◽

Caroline Bianca Santos Tancredi Molina ◽

Paulo Sergio Cugnasca ◽

Joao Batista Camargo ◽

...

Keyword(s):

Artificial Intelligence ◽

Literature Review ◽

Systematic Literature Review ◽

Autonomous Vehicle ◽

Vehicle Safety ◽

The Impact

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Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review

Wireless Communications and Mobile Computing ◽

10.1155/2019/5931315 ◽

2019 ◽

Vol 2019 ◽

pp. 1-20 ◽

Cited By ~ 19

Author(s):

Shah Nazir ◽

Yasir Ali ◽

Naeem Ullah ◽

Iván García-Magariño

Keyword(s):

Internet Of Things ◽

Literature Review ◽

Mobile Computing ◽

Healthcare System ◽

Systematic Literature Review ◽

Research Work ◽

Future Research ◽

Healthcare Environment ◽

Review Protocol ◽

The Impact

The impact of Internet of Things has been revolutionized in all fields of life, but its impact on the healthcare system has been significant due to its cutting edge transition. The role of Internet of Things becomes more dominant when it is supported by the features of mobile computing. The mobile computing extends the functionality of IoT in healthcare environment by bringing a massive support in the form of mobile health (m-health). In this research, a systematic literature review protocol is proposed to study how mobile computing assists IoT applications in healthcare, contributes to the current and future research work of IoT in the healthcare system, brings privacy and security in health IoT devices, and affects the IoT in the healthcare system. Furthermore, the intentions of the paper are to study the impacts of mobile computing on IoT in healthcare environment or smart hospitals in light of our systematic literature review protocol. The proposed study reports the papers that were included based on filtering process by title, abstract, and contents, and a total of 116 primary studies were included to support the proposed research. These papers were then analysed for research questions defined for the proposed study.

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A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective

Human Resource Management Review ◽

10.1016/j.hrmr.2021.100857 ◽

2021 ◽

pp. 100857

Author(s):

Vijay Pereira ◽

Elias Hadjielias ◽

Michael Christofi ◽

Demetris Vrontis

Keyword(s):

Artificial Intelligence ◽

Literature Review ◽

Systematic Literature Review ◽

Process Perspective ◽

The Impact ◽

Workplace Outcomes

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AB0602 IMPACT OF SOCIOECONOMIC FACTORS ON PAIN AND FUNCTION IN KNEE OSTEOARTHRITIS: A SYSTEMATIC LITERATURE REVIEW

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.3634 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1337.2-1337

Author(s):

T. W. Swinnen ◽

M. Willems ◽

I. Jonkers ◽

F. P. Luyten ◽

J. Vanrenterghem ◽

...

Keyword(s):

Risk Factors ◽

Literature Review ◽

Knee Osteoarthritis ◽

Socioeconomic Factors ◽

Systematic Literature Review ◽

Intervention Effects ◽

Socioeconomic Outcomes ◽

And Function ◽

The Impact

Background:The personal and societal burden of knee osteoarthritis (KOA) urges the research community to identify factors that predict its onset and progression. A mechanistic understanding of disease is currently lacking but needed to develop targeted interventions. Traditionally, risk factors for KOA are termed ‘local’ to the joint or ‘systemic’ referring to whole-body systems. There are however clear indications in the scientific literature that contextual factors such as socioeconomic position merit further scientific scrutiny, in order to justify a more biopsychosocial view on risk factors in KOA.Objectives:The aims of this systematic literature review were to assess the inclusion of socioeconomic factors in KOA research and to identify the impact of socioeconomic factors on pain and function in KOA.Methods:Major bibliographic databases, namely Medline, Embase, CINAHL, Web of Science and Cochrane, were independently screened by two reviewers (plus one to resolve conflicts) to identify research articles dealing with socioeconomic factors in the KOA population without arthroplasty. Included studies had to quantify the relationship between socioeconomic factors and pain or function. Main exclusion criteria were: a qualitative design, subject age below 16 years and articles not written in English or Dutch. Methodological quality was assessed via the Cochrane risk of bias tools for randomized (ROB-II) and non-randomized intervention studies (ROBIN-I) and the Newcastle-Ottawa Scale for assessing the quality of non-randomised studies. Due to heterogeneity of studies with respect to outcomes assessed and analyses performed, no meta-analysis was performed.Results:Following de-duplication, 7639 articles were available for screening (120 conflicts resolved without a third reader). In 4112 articles, the KOA population was confirmed. 1906 (25%) were excluded because of knee arthroplasty and 1621 (21%) because of other issues related to the population definition. Socioeconomic factors could not be identified in 4058 (53%) papers and were adjusted for in 211 (3%) articles. In the remaining papers covering pain (n=110) and/or function (n=81), education (62%) and race (37%) were most frequently assessed as socioeconomic factors. A huge variety of mainly dichotomous or ordinal socioeconomic outcomes was found without further methodological justification nor sensitivity analysis to unravel the impact of selected categories. Although the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was the most popular instrument to assess pain and function, data pooling was not possible as socioeconomic factors estimates were part of multilevel models in most studies. Overall results showed that lower education and African American race were consistent predictors of pain and poor function, but those effects diminished or disappeared when psychological aspects (e.g. discrimination) or poverty estimates were taken into account. When function was assessed using self-reported outcomes, the impact of socioeconomic factors was more clear versus performance-based instruments. Quality of research was low to moderate and the moderating or mediating impact of socioeconomic factors on intervention effects in KOA is understudied.Conclusion:Research on contextual socioeconomic factors in KOA is insufficiently addressed and their assessment is highly variable methodologically. Following this systematic literature review, we can highlight the importance of implementing a standardised and feasible set of socioeconomic outcomes in KOA trials1, as well as the importance of public availability of research databases including these factors. Future research should prioritise the underlying mechanisms in the effect of especially education and race on pain and function and assess its impact on intervention effects to fuel novel (non-)pharmacological approaches in KOA.References:[1]Smith TO et al. The OMERACT-OARSI Core Domain Set for Measurement in Clinical Trials of Hip and/or Knee Osteoarthritis J Rheumatol 2019. 46:981–9.Disclosure of Interests:None declared.

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