Technologies in medicine of the future (sociological view)

2020 ◽  
pp. 15-27
Author(s):  
O. Lebed ◽  
N. Prisyazhnaya ◽  
S. Kamaletdinova
Keyword(s):  
Health Economics ◽  
Basic Science ◽  
Medical Insurance ◽  
Medical Specialists ◽  
Sociology Of Medicine ◽  
New Directions ◽  
The Future ◽  
Medical University ◽  
Sociological View

The study of ideas about the future of medicine is one of the new directions of modern sociology of medicine. At the Departmentof sociology of medicine, health economics and medical insurance of the First state medical University, an analysis of the opinions of senior medical specialists was conducted, which showed that the development of medicine is based on its relationship with science. This will require an understanding of the role of basic science in the training of a modern doctor.

scholarly journals The evolution of predictive models and tourism

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Najmeh Gharibi
Keyword(s):  
Technology Acceptance ◽  
Predictive Models ◽  
Future Research ◽  
Content Type ◽  
Technology Acceptance Models ◽  
New Directions ◽  
The Future ◽  
Future Outcomes ◽  
Tourism Services

Purpose This study aims to investigate the predictive technology acceptance models and their evolution in the tourism context. These predictive models make a knowledgeable decision about the possibility of future outcomes by analysing data. As futurists are interested in making a prediction about the likelihood of different behaviours over time, researchers of these predictive models have focussed on behaviour and predicting the intentions of users. This study proposes to demonstrate the revolution of these models and how are changed overtime. It also indicates the role of them in future studies. Design/methodology/approach By reviewing the predictive models and literature, this study looks in-depth in the process of alteration of these models. Findings This study explores the reasons of the evolution of predictive models and how they are changed. It shed light on the role of predictive models in future research and will suggest new directions for forthcoming studies. Research limitations/implications One of the main limitations of this study is that as the world is currently struggling with COVID-19 and predictability of these models will be changed. As the future is disruptive, it cannot be concluded that how these models will be altered in future. Practical implications Role of predictive behavioural models of tourists is fundamentally crucial in assessing the performance of planners and marketers of tourism services in the future. It will also vastly helps the successful development of tourism sectors, and it has practical value for all tourism stakeholders. Originality/value Few studies have focussed on the evaluation of these models and their role in future research.

The Future of the Science of Complex Systems?

2018 ◽  
Author(s):  
Stefan Thurner ◽  
Rudolf Hanel ◽  
Peter Klimekl
Keyword(s):  
Complex Systems ◽  
Scaling Laws ◽  
Evolutionary Dynamics ◽  
First Century ◽  
Mathematical Framework ◽  
New Directions ◽  
The Future ◽  
Universality Classes ◽  
Century Science

The chapter is a mini outlook on the field. The classic achievenments in complexity science are mentioned, and we summarize how the new directions contained in this book might open new doors into a truly twenty-first-century science of complex systems.We do that by clarifying the origin of scaling laws, in particular for driven non-equilibrium systems, deriving the statistics of driven systems on the basis of driving and relaxing processes, categorizing probabilistic complex systems into universality classes, by developing ways for meaningful generalizations of statistical mechanics, and information theory so that they become useful for complex systems, and finally, by unifying the different approaches to evolution and co-evolution into a single mathematical framework that can serve as the basis for understanding co-evolutionary dynamics of states and interactions. We comment on our view of the role of artificial intelligence and our opinion on the future of science of complex systems.

Challenges of Fear Conditioning Research in the Age of RDoC

2017 ◽  
Vol 225 (3) ◽  
pp. 189-199 ◽  
Author(s):  
Tina B. Lonsdorf ◽  
Jan Richter
Keyword(s):  
Fear Conditioning ◽  
Clinical Diagnosis ◽  
Research Domain Criteria ◽  
Major Focus ◽  
The Future ◽  
Definition Of ◽  
Methodological Considerations ◽  
Research Domain

Abstract. As the criticism of the definition of the phenotype (i.e., clinical diagnosis) represents the major focus of the Research Domain Criteria (RDoC) initiative, it is somewhat surprising that discussions have not yet focused more on specific conceptual and procedural considerations of the suggested RDoC constructs, sub-constructs, and associated paradigms. We argue that we need more precise thinking as well as a conceptual and methodological discussion of RDoC domains and constructs, their interrelationships as well as their experimental operationalization and nomenclature. The present work is intended to start such a debate using fear conditioning as an example. Thereby, we aim to provide thought-provoking impulses on the role of fear conditioning in the age of RDoC as well as conceptual and methodological considerations and suggestions to guide RDoC-based fear conditioning research in the future.

The Role of Tradeoff Salience and Connectedness to the Future Self

2011 ◽  
Author(s):  
Daniel Bartels ◽  
Oleg Urminsky ◽  
Shane Frederick
Keyword(s):  
The Future ◽  
Future Self

Role of the future in positive psychology

2013 ◽  
Author(s):  
Mihaly Csikszentmihalyi ◽  
Jeanne Nakamura
Keyword(s):  
Positive Psychology ◽  
The Future
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