Intelligent Medical Decision Support System Based On Imperfect Information PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Intelligent Medical Decision Support System Based On Imperfect Information PDF full book. Access full book title Intelligent Medical Decision Support System Based On Imperfect Information.

Intelligent Medical Decision Support System Based on Imperfect Information

Intelligent Medical Decision Support System Based on Imperfect Information
Author: Krzysztof Dyczkowski
Publisher: Springer
Total Pages: 137
Release: 2017-10-01
Genre: Technology & Engineering
ISBN: 3319670050

Download Intelligent Medical Decision Support System Based on Imperfect Information Book in PDF, ePub and Kindle

This book discusses computer-supported medical diagnosis with a particular focus on ovarian tumor diagnosis – since ovarian cancer is difficult to diagnose and has high mortality rates, especially in Central and Eastern Europe. It presents the theoretical foundations (both medical and mathematical) of the intelligent OvaExpert system, which supports decision-making in tumor diagnosis. OvaExpert was created primarily to help gynecologists predict the malignancy of ovarian tumors by applying the existing diagnostic models and using modern methods of computational intelligence that accommodate imprecise and imperfect medical data, both of which are common features of everyday medical practice. The book presents novel methods based on interval-valued fuzzy sets and the theory of their cardinalities.


Clinical Decision Support System

Clinical Decision Support System
Author: Fouad Sabry
Publisher: One Billion Knowledgeable
Total Pages: 138
Release: 2023-07-06
Genre: Computers
ISBN:

Download Clinical Decision Support System Book in PDF, ePub and Kindle

What Is Clinical Decision Support System A clinical decision support system, often known as a CDSS, is a type of health information technology that offers physicians, staff members, patients, and other individuals access to knowledge and information that is personal to them in order to improve health and health care. The Clinical Decision Support System (CDSS) is comprised of several different applications that improve clinical workflow decision-making. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets, focused patient data reports and summaries, documentation templates, diagnostic support, and contextually appropriate reference information, as well as a variety of other tools. A working definition of "health evidence" has been offered by Robert Hayward of the Centre. It reads as follows: "Clinical decision support systems link health observations with health knowledge to influence health choices by clinicians for improved health care." CDSSs comprise a prominent topic in artificial intelligence in medicine. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Clinical decision support system Chapter 2: Gello Expression Language Chapter 3: International Health Terminology Standards Development Organisation Chapter 4: Medical algorithm Chapter 5: Health informatics Chapter 6: Personal Health Information Protection Act Chapter 7: Treatment decision support Chapter 8: Artificial intelligence in healthcare Chapter 9: Health information technology Chapter 10: Applications of artificial intelligence (II) Answering the public top questions about clinical decision support system. (III) Real world examples for the usage of clinical decision support system in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of clinical decision support system' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of clinical decision support system.


Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and Perspectives

Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and Perspectives
Author: Krassimir T. Atanassov
Publisher: Springer Nature
Total Pages: 457
Release: 2022-02-18
Genre: Technology & Engineering
ISBN: 3030959295

Download Uncertainty and Imprecision in Decision Making and Decision Support: New Advances, Challenges, and Perspectives Book in PDF, ePub and Kindle

This book is composed of selected papers from the Sixteenth National Conference on Operational and Systems Research, BOS-2020, held on December 14-15, 2020, one of premiere conferences in the field of operational and systems research. The second is the Nineteenth International Workshop on Intuitionistic Fuzzy Sets and Generalized Nets, IWIFSGN 2020, held on December 10-11, 2020, in Warsaw, Poland, in turn—one of premiere conferences on fuzzy logic, notably on extensions of the traditional fuzzy sets, also comprising a considerable part on the generalized nets (GNs), an important extension of the traditional Petri nets. A joint publication of selected papers from the two conferences follows a long tradition of such a joint organization and—from a substantial point of view—combines systems modeling, systems analysis, broadly perceived operational research, notably optimization, decision making, and decision support, with various aspects of uncertain and imprecise information and their related tools and techniques.


Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Author: Davide Ciucci
Publisher: Springer Nature
Total Pages: 825
Release: 2022-07-04
Genre: Computers
ISBN: 3031089715

Download Information Processing and Management of Uncertainty in Knowledge-Based Systems Book in PDF, ePub and Kindle

This two-volume set (CCIS 1601-1602) constitutes the proceedings of the 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2021, held in Milan, Italy, in July 2022. The 124 papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections as follows: aggregation theory beyond the unit interval; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy mathematical analysis and its applications; generalized sets and operators; information fusion techniques based on aggregation functions, pre-aggregation functions, and their generalizations; interval uncertainty; knowledge acquisition, representation and reasoning; logical structures of opposition and logical syllogisms; mathematical fuzzy logics; theoretical and applied aspects of imprecise probabilities; data science and machine learning; decision making modeling and applications; e-health; fuzzy methods in data mining and knowledge discovery; soft computing and artificia intelligence techniques in image processing; soft methods in statistics and data analysis; uncertainty, heterogeneity, reliability and explainability in AI; weak and cautious supervised learning.


Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications
Author: Jesús Medina
Publisher: Springer
Total Pages: 773
Release: 2018-05-29
Genre: Computers
ISBN: 3319914790

Download Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications Book in PDF, ePub and Kindle

This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).


Deep Learning for Medical Decision Support Systems

Deep Learning for Medical Decision Support Systems
Author: Utku Kose
Publisher: Springer Nature
Total Pages: 185
Release: 2020-06-17
Genre: Technology & Engineering
ISBN: 981156325X

Download Deep Learning for Medical Decision Support Systems Book in PDF, ePub and Kindle

This book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today’s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation.


Interval-Valued Methods in Classifications and Decisions

Interval-Valued Methods in Classifications and Decisions
Author: Urszula Bentkowska
Publisher: Springer
Total Pages: 163
Release: 2019-02-08
Genre: Technology & Engineering
ISBN: 3030129276

Download Interval-Valued Methods in Classifications and Decisions Book in PDF, ePub and Kindle

This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information.


Uncertainty Data in Interval-Valued Fuzzy Set Theory

Uncertainty Data in Interval-Valued Fuzzy Set Theory
Author: Barbara Pękala
Publisher: Springer
Total Pages: 181
Release: 2018-06-27
Genre: Technology & Engineering
ISBN: 3319939106

Download Uncertainty Data in Interval-Valued Fuzzy Set Theory Book in PDF, ePub and Kindle

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.


Clinical Decision Support Systems

Clinical Decision Support Systems
Author: Eta S. Berner
Publisher: Springer
Total Pages: 270
Release: 2006-11-14
Genre: Medical
ISBN: 9780387339146

Download Clinical Decision Support Systems Book in PDF, ePub and Kindle

This is a resource book on clinical decision support systems for informatics specialists, a textbook for teachers or students in health informatics and a comprehensive introduction for clinicians. It has become obvious that, in addition to physicians, other health professionals have need of decision support. Therefore, the issues raised in this book apply to a broad range of clinicians. The book includes chapters written by internationally recognized experts on the design, evaluation and application of these systems, who examine the impact of computer-based diagnostic tools both from the practitioner’s perspective and that of the patient.


Information Processing and Management of Uncertainty in Knowledge-Based Systems

Information Processing and Management of Uncertainty in Knowledge-Based Systems
Author: Marie-Jeanne Lesot
Publisher: Springer Nature
Total Pages: 816
Release: 2020-06-05
Genre: Computers
ISBN: 3030501434

Download Information Processing and Management of Uncertainty in Knowledge-Based Systems Book in PDF, ePub and Kindle

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.