Information Technology/Artificial Intelligence Innovations Needed for Better Quality of Life in Caregiving Homes

2020 ◽  
pp. 37-58
Author(s):  
Yukiyo Ikeda ◽  
Mutsutaka Kobayakawa ◽  
Hiroshi Nakao ◽  
Fumikazu Iseki ◽  
Hironobu Matsushita
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Information Technology

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

scholarly journals From the First Visit On: Information Technology and Communication

2013 ◽  
Vol 9 (3) ◽  
pp. 152-154 ◽  
Author(s):  
J. Russell Hoverman
Keyword(s):  
Quality Of Life ◽  
Information Technology ◽  
Family Members ◽  
Well Being ◽  
Technology And Communication

The oncology community has found that communication is key to the patient's quality of life, the well-being of family members, hospice enrollment, and costs. The challenge is to make these conversations happen.

scholarly journals Visual control system for grip of glasses oriented to assistance robotics

2020 ◽  
Vol 10 (6) ◽  
pp. 6330
Author(s):  
Robinson Jimenez-Moreno ◽  
Astrid Rubiano ◽  
Jose L. Ramirez
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Control System ◽  
Fuzzy System ◽  
People With Disabilities ◽  
Visual Control ◽  
Liquid Level ◽  
Robotic Arm ◽  
Artificial Intelligence Techniques

Assistance robotics is presented as a means of improving the quality of life of people with disabilities, an application case is presented in assisted feeding. This paper presents the development of a system based on artificial intelligence techniques, for the grip of a glass, so that it does not slip during its manipulation by means of a robotic arm, as the liquid level varies. A faster R-CNN is used for the detection of the glass and the arm's gripper, and from the data obtained by the network, the mass of the beverage is estimated, and a delta of distance between the gripper and the liquid. These estimated values are used as inputs for a fuzzy system which has as output the torque that the motor that drives the gripper must exert. It was possible to obtain a 97.3% accuracy in the detection of the elements of interest in the environment with the faster R-CNN, and a 76% performance in the grips of the glass through the fuzzy algorithm.

Literacy as a Bridge to Quality of Life

2021 ◽  
pp. 25-35
Keyword(s):  
Quality Of Life ◽  
Information Technology ◽  
Lifelong Learning ◽  
21St Century ◽  
Job Market ◽  
Personal Lives ◽  
Key Competencies ◽  
Educational Professional

Information technology spreads through the life of the whole society in the educational, professional, and personal lives. It heightens the requirements for the reader's competence and defines key competencies for the 21st century. The requirement for the successful entry to the job market is increasingly about the competency to handle information technology. The problems in reading are a major source of challenges in the inclusion. Strengthening of the reader's skills and extending the offer for lifelong learning is therefore key for overcoming these challenges. This chapter explores literacy as a bridge to quality of life.

Impact of AI regulation on intention to use robots

2019 ◽  
Vol 8 (2) ◽  
pp. 97-114
Author(s):  
Sheshadri Chatterjee
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Design Methodology ◽  
Regulatory Control ◽  
Control Beliefs ◽  
Intention To Use ◽  
Content Type ◽  
And Control ◽  
The Impact

Purpose The purpose of this paper is to identify the factors influencing the citizens to use robots that would improve the quality of life of the citizens. Design/methodology/approach With the help of different adoption theories and models and with the support of background studies, some hypotheses have been formulated and a conceptual model has been developed with the consideration of the impact of artificial intelligence regulation (IAR) that controls the use of robots as a moderator. The model has been validated and the hypotheses have been tested by statistical analysis with the help of survey works involving consideration of feedbacks from 503 usable respondents. Findings The study reveals that the use of robots by the citizens would appreciably increase if government imposes strict artificial intelligence (AI) regulatory control concerning the use of robots, and in that case, it appears that the use of robots would improve the quality of life of the citizens. Research limitations/implications The duly validated model would help the authority to appropriately nurse and nurture the factors such as ethical dilemma, perceived risks and control beliefs for enhancing the intention of the citizens to use robots for many purposes including domestic usage in the context of appropriate restrictions imposed through AI regulation. Such use of robots would eventually improve the quality of life. Originality/value There are a few studies covering analysis of IAR as a moderator on the linkages of the predictors with the intention of the citizens to use robots. In this context, this study is claimed to have offered a novel contribution.

Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care

2018 ◽  
pp. 1-9 ◽  
Author(s):  
Shivank Garg ◽  
Noelle L. Williams ◽  
Andrew Ip ◽  
Adam P. Dicker
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Health Care ◽  
Data Collection ◽  
Patient Outcomes ◽  
Cancer Care ◽  
Digital Health ◽  
Health Technologies ◽  
Health Care Value

Digital health constitutes a merger of both software and hardware technology with health care delivery and management, and encompasses a number of domains, from wearable devices to artificial intelligence, each associated with widely disparate interaction and data collection models. In this review, we focus on the landscape of the current integration of digital health technology in cancer care by subdividing digital health technologies into the following sections: connected devices, digital patient information collection, telehealth, and digital assistants. In these sections, we give an overview of the potential clinical impact of such technologies as they pertain to key domains, including patient education, patient outcomes, quality of life, and health care value. We performed a search of PubMed ( www.ncbi.nlm.nih.gov/pubmed ) and www.ClinicalTrials.gov for numerous terms related to digital health technologies, including digital health, connected devices, smart devices, wearables, activity trackers, connected sensors, remote monitoring, electronic surveys, electronic patient-reported outcomes, telehealth, telemedicine, artificial intelligence, chatbot, and digital assistants. The terms health care and cancer were appended to the previously mentioned terms to filter results for cancer-specific applications. From these results, studies were included that exemplified use of the various domains of digital health technologies in oncologic care. Digital health encompasses the integration of a vast array of technologies with health care, each associated with varied methods of data collection and information flow. Integration of these technologies into clinical practice has seen applications throughout the spectrum of care, including cancer screening, on-treatment patient management, acute post-treatment follow-up, and survivorship. Implementation of these systems may serve to reduce costs and workflow inefficiencies, as well as to improve overall health care value, patient outcomes, and quality of life.

scholarly journals Artificial Intelligence Research in Singapore: Assisting the Development of a Smart Nation

AI Magazine ◽  
2017 ◽  
Vol 38 (3) ◽  
pp. 102-105 ◽  
Author(s):  
Pradeep Varakantham ◽  
Bo An ◽  
Bryan Low ◽  
Jie Zhang
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Improve Quality ◽  
Artificial Intelligence Research ◽  
Automated Methods

Artificial Intelligence (AI) research in Singapore is focused on accelerating the country’s development into a Smart Nation. Specifically, AI has been employed extensively in either augmenting the intelligence of humans or in developing automated methods and systems to improve quality of life in Singapore.

scholarly journals Analysis of the Impact of Oral Health on Adolescent Quality of Life Using Standard Statistical Methods and Artificial Intelligence Algorithms

Children ◽  
2021 ◽  
Vol 8 (12) ◽  
pp. 1156
Author(s):  
Milica Gajic ◽  
Jovan Vojinovic ◽  
Katarina Kalevski ◽  
Maja Pavlovic ◽  
Veljko Kolak ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Oral Health ◽  
Statistical Methods ◽  
Life Quality ◽  
Total Sample ◽  
Serbian Version ◽  
Value Decomposition ◽  
The Impact

The aim of this study was to determine the impact of oral health on adolescent quality of life and to compare the results obtained using standard statistical methods and artificial intelligence algorithms. In order to measure the impact of oral health on adolescent quality of life, a validated Serbian version of the Oral Impacts on Daily Performance (OIDP) scale was used. The total sample comprised 374 respondents. The obtained results were processed using standard statistical methods and machine learning, i.e., artificial intelligence algorithms—singular value decomposition. OIDP score was dichotomized into two categories depending on whether the respondents had or did not have oral or teeth problems affecting their life quality. Human intuition and machine algorithms came to the same conclusion on how the respondents should be divided. As such, method quality and the need to perform analyses of this type in dentistry studies were demonstrated. Using artificial intelligence algorithms, the respondents can be clustered into characteristic groups that allow the discovery of details not possible with the intuitive division of respondents by gender.

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