Considerations on the Factors Influencing Living Kidney Donors' Autonomous Decision-Making: A Systematic Literature Review

2018 ◽  
Vol 50 (10) ◽  
pp. 3036-3044
Author(s):  
N. Arai ◽  
Y. Takimoto ◽  
E. Nakazawa ◽  
A. Akabayashi
2021 ◽  
Vol 27 (4) ◽  
pp. 146045822110523
Author(s):  
Nicholas RJ Möllmann ◽  
Milad Mirbabaie ◽  
Stefan Stieglitz

The application of artificial intelligence (AI) not only yields in advantages for healthcare but raises several ethical questions. Extant research on ethical considerations of AI in digital health is quite sparse and a holistic overview is lacking. A systematic literature review searching across 853 peer-reviewed journals and conferences yielded in 50 relevant articles categorized in five major ethical principles: beneficence, non-maleficence, autonomy, justice, and explicability. The ethical landscape of AI in digital health is portrayed including a snapshot guiding future development. The status quo highlights potential areas with little empirical but required research. Less explored areas with remaining ethical questions are validated and guide scholars’ efforts by outlining an overview of addressed ethical principles and intensity of studies including correlations. Practitioners understand novel questions AI raises eventually leading to properly regulated implementations and further comprehend that society is on its way from supporting technologies to autonomous decision-making systems.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alan Brnabic ◽  
Lisa M. Hess

Abstract Background Machine learning is a broad term encompassing a number of methods that allow the investigator to learn from the data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision making. Methods This systematic literature review was conducted to identify published observational research of employed machine learning to inform decision making at the patient-provider level. The search strategy was implemented and studies meeting eligibility criteria were evaluated by two independent reviewers. Relevant data related to study design, statistical methods and strengths and limitations were identified; study quality was assessed using a modified version of the Luo checklist. Results A total of 34 publications from January 2014 to September 2020 were identified and evaluated for this review. There were diverse methods, statistical packages and approaches used across identified studies. The most common methods included decision tree and random forest approaches. Most studies applied internal validation but only two conducted external validation. Most studies utilized one algorithm, and only eight studies applied multiple machine learning algorithms to the data. Seven items on the Luo checklist failed to be met by more than 50% of published studies. Conclusions A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of machine learning methods to inform patient-provider decision making. There is a need to ensure that multiple machine learning approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that decisions for patient care are being made with the highest quality evidence. Future work should routinely employ ensemble methods incorporating multiple machine learning algorithms.


2021 ◽  
Vol 13 (2) ◽  
pp. 737
Author(s):  
Indre Siksnelyte-Butkiene ◽  
Dalia Streimikiene ◽  
Tomas Balezentis ◽  
Virgilijus Skulskis

The European Commission has recently adopted the Renovation Wave Strategy, aiming at the improvement of the energy performance of buildings. The strategy aims to at least double renovation rates in the next ten years and make sure that renovations lead to higher energy and resource efficiency. The choice of appropriate thermal insulation materials is one of the simplest and, at the same time, the most popular strategies that effectively reduce the energy demand of buildings. Today, the spectrum of insulation materials is quite wide, and each material has its own specific characteristics. It is recognized that the selection of materials is one of the most challenging and difficult steps of a building project. This paper aims to give an in-depth view of existing multi-criteria decision-making (MCDM) applications for the selection of insulation materials and to provide major insights in order to simplify the process of methods and criteria selection for future research. A systematic literature review is performed based on the Search, Appraisal, Synthesis and Analysis (SALSA) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. In order to determine which MCDM method is the most appropriate for different questions, the main advantages and disadvantages of different methods are provided.


2021 ◽  
Vol 13 (8) ◽  
pp. 4129
Author(s):  
Manuel Sousa ◽  
Maria Fatima Almeida ◽  
Rodrigo Calili

Multiple-criteria decision making (MCDM) methods have been widely employed in various fields and disciplines, including decision problems regarding Sustainable Development (SD) issues. The main objective of this paper is to present a systematic literature review (SLR) on MCDM methods supporting decisions focusing on the achievement of UN Sustainable Development Goals (SDGs) and the implementation of the 2030 Agenda for Sustainable Development in regional, national, or local contexts. In this regard, 143 published scientific articles from 2016 to 2020 were retrieved from the Scopus database, selected and reviewed. They were categorized according to the decision problem associated with SDGs issues, the MCDM methodological approach, including the use (or not) of fuzzy set theory, sensitivity analysis, and multistakeholder approaches, the context of MCDM applications, and the MCDM classification (if utility-based, compromise, multi-objective, outranking, or other MCDM methods). The widespread adoption of MCDM methods in complex contexts confirms that they can help decision-makers solve multidimensional problems associated with key issues within the 2030 Agenda framework. Besides, the state-of-art review provides an improved understanding of this research field and directions for building a research agenda for those interested in advancing the research on MCDM applications in issues associated with the 2030 Agenda framework.


2019 ◽  
Author(s):  
deli rahmadani ◽  
Rusdinal ◽  
Hade Afriansyah

Abstract - This article aims to explain some things about decision making. The methodology used to regulate this article is Systematic Literature Review (SLR). Researchers search from several trusted sources and then analyze it. The results of this article are based on the analysis of researchers in general there are several things.


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