A Survey of Robots in Healthcare

Kyrarini, Maria; Lygerakis, Fotios; Rajavenkatanarayanan, Akilesh; Sevastopoulos, Christos; Nambiappan, Harish Ram; Chaitanya, Kodur Krishna; Babu, Ashwin Ramesh; Mathew, Joanne; Makedon, Fillia

doi:10.3390/technologies9010008

Cited by 239 publications

(94 citation statements)

References 103 publications

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“…Healthcare robots are intelligent machines used in healthcare settings [31]. However, their functions and performance are still continually being developed [32]. The complexity of nursing phenomena is compounded with the introduction of healthcare robots.…”

Section: Model For the Intermediary Role Of Nurses In Transactive Relationships With Healthcare Robotsmentioning

confidence: 99%

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology

Tanioka

Locsin

Betriana

et al. 2021

IJERPH

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The growing use of robots in nursing and healthcare facilities has prompted increasing research on human–robot interactions. However, specific research designs that can guide researchers to conduct rigorous investigations on human–robot interactions are limited. This paper aims to discuss the development and application of a new research design—the Intentional Observational Clinical Research Design (IOCRD). Data sources to develop the IOCRD were derived from surveyed literature of the past decade, focusing on clinical nursing research and theories relating robotics to nursing and healthcare practice. The distinction between IOCRD and other research design is the simultaneous data generation collected using advanced technological devices, for example, the wireless Bonaly-light electrocardiogram (ECG) to track heart rate variability of research subjects, robot application programs on the iPad mini to control robot speech and gestures, and Natural Language Processing programs. Even though IOCRD was developed for human–robot research, there remain vast opportunities for its use in nursing practice and healthcare. With the unique feature of simultaneous data generation and analysis, an interdisciplinary collaborative research team is strongly suggested. The IOCRD is expected to contribute guidance for researchers in conducting clinical research related to robotics in nursing and healthcare.

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Section: Model For the Intermediary Role Of Nurses In Transactive Relationships With Healthcare Robotsmentioning

confidence: 99%

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology

Tanioka

Locsin

Betriana

et al. 2021

IJERPH

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“…Furthermore, with the increasing amount of data available, especially in oncology, Electronic Health Records (EHRs) are now being designed to manage and correlate the different patient profiles by using predictive models such as SVM, ANNs, etc. [ 27 ]. The machine learning algorithms can easily sort through and learn from the vast range of treatments available and combine them with the patient’s genetics and medical history to suggest the best possible treatment for them.…”

Section: Recent Ai Contributions In Healthcarementioning

confidence: 99%

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions

Pandya

Thakur

Saxena

et al. 2021

Sensors

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The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medical Things), genetic intelligence algorithms, smart immunological methodologies, etc., has made this process easier. These technologies can observe relations and patterns that humans do and recognize patterns that are unobservable by humans. Furthermore, these technologies have also enabled us to understand better the different types of cells in the immune system, their structures, their importance, and their impact on our immunity, particularly in the case of debilitating diseases such as cancer. The undertaken study explores the AI methodologies currently in the field of immunology. The initial part of this study explains the integration of AI in healthcare and how it has changed the face of the medical industry. It also details the current applications of AI in the different healthcare domains and the key challenges faced when trying to integrate AI with healthcare, along with the recent developments and contributions in this field by other researchers. The core part of this study is focused on exploring the most common classifications of health diseases, immunology, and its key subdomains. The later part of the study presents a statistical analysis of the contributions in AI in the different domains of immunology and an in-depth review of the machine learning and deep learning methodologies and algorithms that can and have been applied in the field of immunology. We have also analyzed a list of machine learning and deep learning datasets about the different subdomains of immunology. Finally, in the end, the presented study discusses the future research directions in the field of AI in immunology and provides some possible solutions for the same.

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“…Robot execution in the fight against COVID-19 has acquired positive criticism from medical services laborers for its potential in obstructing disease and is successful in easing clinical specialists from rehashed undertakings 20 . The cultural effect of robots is fundamental as they may impact the nature of medical care for patients, and the nature of work for guardians and their potential security concerns stay to be addressed 25 . AS PC processors and capacity get quicker and less expensive, and as new advances arise in machine learning and multimodal preparing, a universe of plausibility exists for robots perpetually skilled and agile in the human social environment 26 .…”

Section: Barriersmentioning

confidence: 99%

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2021

IJPSR

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A Survey of Robots in Healthcare

Cited by 239 publications

References 103 publications

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology

A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions

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