| 1. |
- Klašnja-Milićević, Aleksandra, et al.
(författare)
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Personalization and adaptation in e-learning systems
- 2017
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Ingår i: Intelligent Systems Reference Library. - Cham : Springer International Publishing. - 1868-4408 .- 1868-4394. ; 112, s. 21-25
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Personalization is a feature that occurs separately within each system that supports some kind of users’ interactions with the system. Generally speaking term “Personalization” means the process of deciding what the highest value of an individual is if (s)he has a set of possible choices. These choices can range from a customized home page “look and feel” to product recommendations or from banner advertisements to news content. In this monograph we are interested in personalization in educational settings. The topic of personalization is strictly related to the shift from a teacher-centred perspective of teaching to a learner-centred, competency-oriented one. Two main approaches to the personalization can be distinguished: user-profile based personalization and rules-based personalization. In the first case this is the process of making decisions based upon stored user profile information or predefined group membership. In the second case this is the process of making decisions based on pre-defined business rules as they apply to a segmentation of users. This chapter presents the most popular adaptation forms of educational materials to learners.
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| 2. |
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Knowledge-Based Systems in Biomedicine and Computational Life Science
- 2012
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: personalized stress diagnosis system, image analysis system for breast cancer diagnosis, analysis of neuronal cell images, structure prediction of protein, relationship between two mental disorders, detection of cardiac abnormalities, holistic medicine based treatment and analysis of life-science data.
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| 3. |
- Mahdiraji, Saeid Amouzad, et al.
(författare)
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An Optimization Model for the Tradeoff Between Efficiency and Equity for Mobile Stroke Unit Placement
- 2021
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Ingår i: Innovation in Medicine and Healthcare. - Singapore : Springer. - 2190-3026 .- 2190-3018. - 9789811630125 - 9789811630132 ; , s. 183-193
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Konferensbidrag (refereegranskat)abstract
- A mobile stroke unit (MSU) is an ambulance, where stroke patients can be diagnosed and treated. Recently, placement of MSUs has been studied focusing on either maximum population coverage or equal service for all patients, termed efficiency and equity, respectively. In this study, we propose an unconstrained optimization model for the placement of MSUs, designed to introduce a tradeoff between efficiency and equity. The tradeoff is based on the concepts of weighted average time to treatment and the time difference between the expected time to treatment for different geographical areas. We conduct a case-study for Sweden’s Southern Health care Region (SHR), generating three scenarios (MSU1, MSU2, and MSU3) including 1, 2, and 3 MSUs, respectively. We show that our proposed optimization model can tune the tradeoff between the efficiency and equity perspectives for the MSU(s) allocation. This enables a high level of equal service for most inhabitants, as well as reducing the time to treatment for most inhabitants of a geographic region. In particular, placing three MSUs in the SHR with the proposed tradeoff, the share of inhabitants who are expected to receive treatment within an hour potentially improved by about a factor of 14 in our model.
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| 4. |
- Pham, Tuan D, et al.
(författare)
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Knowledge-Based Systems in Biomedicine and Computational Life Science
- 2013. - 1
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Bok (övrigt vetenskapligt/konstnärligt)abstract
- This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: personalized stress diagnosis system, image analysis system for breast cancer diagnosis, analysis of neuronal cell images, structure prediction of protein, relationship between two mental disorders, detection of cardiac abnormalities, holistic medicine based treatment and analysis of life-science data.
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| 5. |
- Qu, Xiaobo, 1983, et al.
(författare)
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Preface
- 2019
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Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 149, s. vii-vii
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 6. |
- Qu, Xiaobo, 1983, et al.
(författare)
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Preface
- 2020
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Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 185, s. v-v
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 7. |
- Qu, Xiaobo, 1983, et al.
(författare)
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Preface
- 2021
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Ingår i: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 231, s. v-vi
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 8. |
- Rakus-Andersson, Elisabeth, et al.
(författare)
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Computational Intelligence in Medical Decisions Making
- 2009
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Ingår i: Recent Advances in Decision Making. - Berlin Heidelberg : Springer verlag. - 9783642021862 ; , s. 145-159
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Bokkapitel (refereegranskat)abstract
- Computation intelligence paradigms including artificial neural networks, fuzzy systems, evolutionary computing techniques, intelligent agents and so on provide a basis for human like reasoning in medical systems. Approximate reasoning is one of the most effective fuzzy systems. The compositional rule of inference founded on the logical law modus ponens is furnished with a true conclusion, provided that the premises of the rule are true as well. Even though there exist different approaches to an implication, being the crucial part of the rule, we modify the early implication proposed in our practical model concerning a medical application. The approximate reasoning system presented in this work considers evaluation of a risk in the situation when physicians weigh necessity of the operation on a patient. The patient’s clinical symptom levels, pathologically heightened, indicate the presence of a disease possible to recover by surgery. We wish to evaluate the extension of the operation danger by involving particularly designed fuzzy sets in the algorithm of approximate reasoning.
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| 9. |
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Recent Advances in Decision Making
- 2009
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- The series Studies in Computational Intelligence (SCI) publishes new developments and advances in the various areas of computational intelligence – quickly and with a high quality. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in com putational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems and hybrid intelligent systems. Critical to both contributors and readers are the short publication time and world-wide distribution – this permits a rapid and broad dissemina tion of research results. springer.com Intelligent paradigms are increasing finding their ways in the design and development of decision support systems. This book presents a sample of recent research results from key researchers. The contributions include: • Introduction to intelligent systems in decision making • A new method of ranking intuitionistic fuzzy alternatives • Fuzzy rule base model identification by bacterial memetic algorithms • Discovering associations with uncertainty from large databases • Dempster-Shafer structures, monotonic set measures and decision making • Interpretable decision-making models • A General methodology for managerial decision making • Supporting decision making via verbalization of data analysis results using linguistic data summaries • Computational intelligence in medical decisions making This book is directed to the researchers, graduate students, professors, decision makers and to those who are interested to investigate intelligent paradigms in decision making.
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| 10. |
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