Customized Web-based System for Elderly People Using Elements of Artificial Intelligence

Babič, František; Jancus, Adrian; Melisova, Katarina

doi:10.15439/2016f165

Cited by 2 publications

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such system would improve the quality of diagnosis, lower the cost of the diagnostic process and could be wildly used by medical staff. Such systems are being developed in a vast field of medical and healthcare areas: [29], [30].…”

Section: Wx Advantagementioning

confidence: 99%

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

Tojza

Redlarski

Janiak

2018

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

This paper presents a new approach to computer supported esophageal pH-metry measurement analysis performed in order to diagnose gastroesophageal reflux disease. In this approach wavelet analysis was used to analyse the esophageal pH-metry course. The research was performed on three groups of pH-metry courses: whole 24-hour pH-metry course, sleep only pH-metry course and 20 minutes after the end of a meal pHmetry course. After performing a 128 level decomposition of the pH-metry course, the Wx was defined as a parameter of extreme differential. This parameter was used to distinguish patients esophageal pH-metry results and on that basis classify patients as healthy or sick. Using this method the sensitivity of 77% was achieved.

show abstract

Section: Wx Advantagementioning

confidence: 99%

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

Tojza

Redlarski

Janiak

2018

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

show abstract

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

et al. 2021

View full text Add to dashboard Cite

Background Artificial intelligence (AI) holds the promise of supporting nurses’ clinical decision-making in complex care situations or conducting tasks that are remote from direct patient interaction, such as documentation processes. There has been an increase in the research and development of AI applications for nursing care, but there is a persistent lack of an extensive overview covering the evidence base for promising application scenarios. Objective This study synthesizes literature on application scenarios for AI in nursing care settings as well as highlights adjacent aspects in the ethical, legal, and social discourse surrounding the application of AI in nursing care. Methods Following a rapid review design, PubMed, CINAHL, Association for Computing Machinery Digital Library, Institute of Electrical and Electronics Engineers Xplore, Digital Bibliography & Library Project, and Association for Information Systems Library, as well as the libraries of leading AI conferences, were searched in June 2020. Publications of original quantitative and qualitative research, systematic reviews, discussion papers, and essays on the ethical, legal, and social implications published in English were included. Eligible studies were analyzed on the basis of predetermined selection criteria. Results The titles and abstracts of 7016 publications and 704 full texts were screened, and 292 publications were included. Hospitals were the most prominent study setting, followed by independent living at home; fewer application scenarios were identified for nursing homes or home care. Most studies used machine learning algorithms, whereas expert or hybrid systems were entailed in less than every 10th publication. The application context of focusing on image and signal processing with tracking, monitoring, or the classification of activity and health followed by care coordination and communication, as well as fall detection, was the main purpose of AI applications. Few studies have reported the effects of AI applications on clinical or organizational outcomes, lacking particularly in data gathered outside laboratory conditions. In addition to technological requirements, the reporting and inclusion of certain requirements capture more overarching topics, such as data privacy, safety, and technology acceptance. Ethical, legal, and social implications reflect the discourse on technology use in health care but have mostly not been discussed in meaningful and potentially encompassing detail. Conclusions The results highlight the potential for the application of AI systems in different nursing care settings. Considering the lack of findings on the effectiveness and application of AI systems in real-world scenarios, future research should reflect on a more nursing care–specific perspective toward objectives, outcomes, and benefits. We identify that, crucially, an advancement in technological-societal discourse that surrounds the ethical and legal implications of AI applications in nursing care is a necessary next step. Further, we outline the need for greater participation among all of the stakeholders involved.

show abstract

Customized Web-based System for Elderly People Using Elements of Artificial Intelligence

Cited by 2 publications

References 17 publications

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

Supporting gastroesophageal reflux disease diagnostics by using wavelet analysis in esophageal pH-metry

Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review

Contact Info

Product

Resources

About