scholarly journals An Intelligent Decision-Making Support System for the Detection and Staging of Prostate Cancer in Developing Countries

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Jun Zhang ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Kanghuai Liu
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Developing Countries ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Diagnostic System ◽  
Medical Personnel ◽  
Medical Systems ◽  
Intelligent Decision Making ◽  
Diagnosis Rate

Most developing countries face huge challenges in the medical field; scarce medical resources and inadequate medical personnel will affect the development and stability of the society. Therefore, for most developing countries, the development of intelligent medical systems can greatly alleviate the social contradictions arising from this problem. In this study, a new data decision-making intelligent system for prostate cancer based on perceptron neural network is proposed, which mainly makes decisions by associating some relevant disease indicators and combining them with medical images. Through data collection, analysis and integration of medical data, as well as the disease detection and decision-making process, patients are given an auxiliary diagnosis and treatment, so as to solve the problems and social contradictions faced by most developing countries. Through the study of hospitalization information of more than 8,000 prostate patients in three hospitals, about 2,156,528 data items were collected and compiled for experiment purposes. Experimental data shows that when the patient base increases from 200 to 8,000, the accuracy of the machine-assisted diagnostic system will increase from 61% to 87%, and the doctor’s diagnosis rate will be reduced to 81%. From the study, it is concluded that when the patient base reaches a certain number, the diagnostic accuracy of the machine-assisted diagnosis system will exceed the doctor’s expertise. Therefore, intelligent systems can help doctors and medical experts treat patients more effectively.

scholarly journals An intelligent decision-making support system for the detection and staging of prostate cancer in developing countries

2020 ◽  
Author(s):  
Jun Zhang ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Kanghuai Liu
Keyword(s):  
Prostate Cancer ◽  
Experimental Data ◽  
Decision Making ◽  
Developing Countries ◽  
Intelligent System ◽  
Medical System ◽  
Image Feature ◽  
Final Decision ◽  
Medical Systems ◽  
Cancer Data

Abstract Background Most developing countries face great problems in the medical, and the threat posed by large populations, scarce medical resources and inadequate medical personnel will affect the development and stability of the society. Therefore, for most developing countries, the development of intelligent medical systems can greatly alleviate the social contradictions arising from this problem. Intelligent Medical System is a system to assist doctors to make decisions. Through effective input, the system makes corresponding decisions and provides doctors with corresponding auxiliary diagnosis and relevant treatment plans. Methods The experimental team collected and compiled about 2,156,528 data items based on the hospitalization information of more than 8,000 prostate patients in three hospitals of Xiangya. The ratio of experimental data to test data was about 7: 3. Combining prostate cancer images and physical indicators to assist diagnosis and make decisions, from the extraction of corresponding image feature data to the final diagnosis decision, a new intelligent system for prostate cancer data decision-making based on Perceptron neural network is proposed. In the comprehensive decision-making, the final decision is made by using the rule-reasoning model. Through data collection, medical data analysis and integration, image processing and analysis, and disease detection and decision-making processes, patients are assisted in diagnosis and treatment to solve the problems and social contradictions facing most developing countries. Results Through the study of hospitalization information of more than 8,000 prostate patients in three hospitals, about 2,156,528 data items were collected and compiled for experiment purposes. Experimental data shows that when the patient base increases from 200 to 8,000, the accuracy of the machine-assisted diagnostic system will increase from 61% to 87%, and the doctor's diagnosis rate will be reduced to 81%. Conclusions From the study, it is concluded that when the patient base reaches a certain number, the diagnostic accuracy of the machine-assisted diagnosis system will exceed the doctor's expertise. So the smart medical system can help doctors and Medical experts make suggest more effective treatments.

scholarly journals Big Medical Data Decision-Making Intelligent System Exploiting Fuzzy Inference Logic for Prostate Cancer in Developing Countries

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 2348-2363 ◽  
Author(s):  
Kanghuai Liu ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Yanlin Tan ◽  
Leilei Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Developing Countries ◽  
Fuzzy Inference ◽  
Intelligent System ◽  
Medical Data

scholarly journals Research on the Framework of Intelligent Command Decision System for Flood Control

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Yao Zhang
Keyword(s):  
Decision Making ◽  
Intelligent Systems ◽  
Flood Control ◽  
Intelligent System ◽  
Decision Makers ◽  
Intelligent Decision Making ◽  
Related Information ◽  
Control Command ◽  
Decision Making System ◽  
Key Issues

Starting from the process of flood control and flood control decision-making, the shortcomings of the traditional flood control and flood control command and decision-making system are analyzed, and an intelligent decision-making system for flood control and flood control is proposed. The structure and functions of the system framework are elaborated in detail, and the key issues in the process of building intelligent systems are pointed out. Based on the real-time information monitoring system, this intelligent system can predict the next phase of hydrometeorology, flood and other related information, help decision makers to identify risks, and optimize the best flood control dispatching plan for decision makers to choose.

A Rollout Control Algorithm for Discrete-Time Stochastic Systems

2010 ◽  
Author(s):  
Andreas A. Malikopoulos
Keyword(s):  
Decision Making ◽  
Markov Chain ◽  
Intelligent Systems ◽  
Control Algorithm ◽  
Stochastic Systems ◽  
Intelligent System ◽  
Control Policy ◽  
Suboptimal Control ◽  
Sequential Decision ◽  
Significant Research

The growing demand for making autonomous intelligent systems that can learn how to improve their performance while interacting with their environment has induced significant research on computational cognitive models. Computational intelligence, or rationality, can be achieved by modeling a system and the interaction with its environment through actions, perceptions, and associated costs. A widely adopted paradigm for modeling this interaction is the controlled Markov chain. In this context, the problem is formulated as a sequential decision-making process in which an intelligent system has to select those control actions in several time steps to achieve long-term goals. This paper presents a rollout control algorithm that aims to build an online decision-making mechanism for a controlled Markov chain. The algorithm yields a lookahead suboptimal control policy. Under certain conditions, a theoretical bound on its performance can be established.

Updated Architectures for the Integration of Decision Making Support Functionalities

2011 ◽  
pp. 3884-3889 ◽  
Author(s):  
Guisseppi A. Forgionne
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Intelligent Systems ◽  
Data Access ◽  
Robust Decision Making ◽  
Intelligent Support ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
New Literature ◽  
Decision Making Support

Information systems research continues to examine ways to improve support for decision making. The evolution from simple data access and reporting to complex analytical, creative, and artificially intelligent support for decision making persists (Holsapple & Whinston, 1996). In the evolution, existing information systems still, and new intelligent systems have been created to, provide the desired decision making support. By studying the existing, and new, systems’ characteristics, advantages, and disadvantages, researchers and practitioners can better design, develop, and implement robust decision making support systems (Kumar, 1999). The original article facilitated such study by presenting and illustrating the underlying information system architectures for robust decision making support (Forgionne, 2005). This article updates the original by offering additional contributions to the subject. New literature on intelligent decision making support is examined, and the relevant findings are discussed. The title has been modified slightly to reflect the updates.

scholarly journals Situational analysis model in an intelligent system based on multi-agent neurocognitive architectures

2021 ◽  
Vol 2131 (2) ◽  
pp. 022103
Author(s):  
Z Nagoev ◽  
I Pshenokova ◽  
O Nagoeva ◽  
S Kankulov
Keyword(s):  
Decision Making ◽  
Control Systems ◽  
Intelligent System ◽  
Situational Analysis ◽  
Analysis Model ◽  
Intelligent Decision Making ◽  
Intelligent Software ◽  
Intelligent Decision ◽  
Multi Agent ◽  
And Control

Abstract An approach to the development of intelligent decision-making and control systems based on the hypothesis of the organization of neural activity of the brain in the process of performing cognitive functions is proposed. This approach, based on intelligent software agents with a developed cognitive architecture, is able to provide the process of extracting knowledge from an unstructured data flow, generalizing the knowledge and learning gained, to implement effective methods of synthesizing behavior aimed at solving various problems. A multi-agent model of situational analysis based on self-organization of distributed recursive neurocognitive architectures is presented. In particular, the basic principles of situational analysis based on multi-agent neurocognitive architectures are formulated and an algorithm for the preventive synthesis of the behavior of an intelligent agent aimed at avoiding negative situations for itself is developed. The performed computational experiment showed that on the basis of training the neurocognitive architecture by forming new agents-neurons and connections between them, a complex logical function of behavior control (in particular, situational analysis) develops (forms). The results of this study can be used to create intelligent decision-making and control systems for autonomous robots and robotic systems for various purposes.

scholarly journals Sistem Pendukung Keputusan Prediksi Kecepatan Studi Mahasiswa Menggunakan Metode ID3

2011 ◽  
Vol 2 (2) ◽  
Author(s):  
Ronny Ardi Giovani ◽  
Paulus Mudjihartono ◽  
Pranowo Pranowo
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Computer Science ◽  
Support System ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Speed Prediction ◽  
Past Data ◽  
Tree Development

Abstract. Decision Support System of Students’ Study Speed Prediction Using ID3 Method. Speed can be a decisive period of study a student taking a degree in sajana. In this study would be built applications that serve to speed decision making predictions Students study Computer Science University of Atma Jaya Yogyakarta. Students will be expected sooner or later than the period of study by taking one course or thesis that will be undertaken after a certain semesters. There are many methods of classification of one method of ID3 (Induction Decision 3 'Tree'). Development system in this study made use of intelligent systems-based applications. The results achieved after the system is formed, among others, sophisticated and intelligent system capable of storing past data is used as a reference for decision making, where students with certain criteria can know the travel time of their studies, and can refer to the database so the system can be more detailed and rigorous in determining the choice. Keywords: study period speed, Decision Support Systems, ID3, Intelligent Systems Kecepatan masa studi dapat menjadi penentu seorang mahasiswa dalam menempuh gelar sajana. Dalam penelitian ini akan dibangun aplikasi yang berfungsi untuk pengambilan keputusan prediksi kecepatan studi Mahasiswa Teknik Informatika Universitas Atma Jaya Yogyakarta. Mahasiswa akan diprediksi  cepat atau lambatnya masa studi dalam menempuh mata kuliah maupun skripsi yang akan dijalani setelah semester tertentu. Ada banyak metode klasifikasi salah satunya metode ID3 (Induction Decision 3 ‘Tree’). Pembangunan sistem dalam penelitian ini dibuat menggunakan aplikasi berbasis sistem  cerdas. Hasil yang dicapai setelah sistem ini terbentuk antara lain sistem canggih dan cerdas yang mampu menyimpan data masa lalu yang digunakan sebagai acuan pengambilan keputusan, dimana mahasiswa dengan kriteria tertentu dapat diketahui masa tempuh studi mereka, serta dapat mengacu pada database sehingga sistem dapat lebih detail serta teliti dalam menentukan pilihan. Kata Kunci: kecepatan masa studi, Sistem Pendukung Keputusan, ID3, Sistem Cerdas

Cultural Intelligence-Investigation of Different Systems for Heritage Sustainable Preservation

2020 ◽  
Vol 9 (2) ◽  
pp. 16-30
Author(s):  
Anastasia Kioussi ◽  
Anastasios Doulamis ◽  
Maria Karoglou ◽  
Antonia I. Moropoulou
Keyword(s):  
Decision Making ◽  
Intelligent Systems ◽  
Intervention Study ◽  
Cultural Value ◽  
Linear Classifiers ◽  
Intelligent Decision Making ◽  
Complex Process ◽  
Intelligent Decision ◽  
Wide Range ◽  
Feed Forward Neural Networks

Cultural heritage protection is a multidisciplinary subject. An intelligent decision-making mechanism, combined with multi-criteria assessment, is required to lead to compatible and sustainable decision making concerning conservation works. Decision making is a complex process that takes into account a wide range of parameters, from qualitative (such as the historical or cultural value of the building) to quantified data (such as the properties of its materials) and involves the following tasks: monitoring, inspection, diagnosis, intervention study, interventions, and evaluation of interventions. It should be based on specific specifications, criteria, and methodology to ensure the sustainability of the construction and require the availability of data of a different nature and of high quality. In this work, different artificial intelligent systems are investigated and tested—UTASTAR methodology based on linear regression, unsupervised non-linear classifiers (feed-forward neural networks), and clustering methodologies (fuzzy c-means algorithm)—in order to develop a decision.

Mission Performance Aids

2015 ◽  
pp. 190-218
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Cumulative Effect ◽  
Critical Events ◽  
Operational Conditions ◽  
Operational Decision Making ◽  
Mission Critical ◽  
Flight Deck

Flight deck displays that automatically adapt themselves to changing operational conditions are referred to as mission adaptive displays, or smart cockpits. A smart cockpit is an intelligent system possessing advanced reasoning capabilities. Mission Performance Aids are a particular manifestation of Mission Adaptive Displays. Mission Performance Aids fall into three categories: Precision Maneuver Guidance (PMG), Mission Performance Evaluator (MPE), and Operational Decision Making (ODM). The MPE alerts the crew to parameter exceedance. The ODM can calculate a cumulative effect with respect to two or more risk factors being encountered simultaneously. They discern all mission critical events, including escape maneuvers. Currently, this type of performance aid is not available. So this section should prove especially useful for designers of advanced intelligent systems.

INTELLIGENT SYSTEM FOR DIAGNOSING THE PARAMETERS OF THE TECHNICAL CONDITION OF TRACTORS

2021 ◽  
pp. 45-50
Author(s):  
MIKHAIL N. EROKHIN ◽  
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Diagnostic System ◽  
Technical Condition ◽  
Diagnostic Process ◽  
Agricultural Machinery ◽  
Online Mode ◽  
Effi Ciency ◽  
Agricultural Tractors

Research aimed at the development and implementation of new digital methods and intelligent systems that allow improving the diagnostic process, increasing the reliability of determining the functional characteristics of agricultural tractors in an online mode is an important and relevant component of technologies and tools for servicing agricultural machinery. The paper presents the results on the justifi cation and development of an intelligent system for diagnosing machines based on the interaction of a neural network. The advantage of this diagnostic system is the ability to maintain the working condition of agricultural machinery, in case the processes of diagnosis and analysis of the obtained data are automated. The use of an intelligent tractor diagnostic system provides for the determination of not only the cause of failure by the controlled parameters, but also the effi ciency evaluation of the machine as a whole. It is established that one of the ways to increase the effi ciency of using agricultural machinery is the non-contact determination of the parameters of the technical condition of equipment through the modernization of the technology for monitoring the technical condition of machines and the quality of work on the basis of the introduction of modern intelligent and telemetric systems.

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