scholarly journals ORDER PLANNING DECISION SUPPORT SYSTEM FOR CUSTOMER DRIVEN MANUFACTURING: OVERVIEW OF MAIN SYSTEM REQUIREMENTS

2004 ◽  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Main System ◽  
Planning Decision ◽  
System Requirements

Predictive modelling analysis for development of a radiotherapy decision support system in prostate cancer: a preliminary study

2017 ◽  
Vol 16 (2) ◽  
pp. 161-170 ◽  
Author(s):  
Kwang Hyeon Kim ◽  
Suk Lee ◽  
Jang Bo Shim ◽  
Kyung Hwan Chang ◽  
Yuanjie Cao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Support ◽  
Decision Tree ◽  
Decision Support System ◽  
Support System ◽  
Predictive Modelling ◽  
Radiotherapy Planning ◽  
Support Vector ◽  
Toxicity Prediction ◽  
Planning Decision

AbstractPurposeThe aim of this study is to develop predictive models to predict organ at risk (OAR) complication level, classification of OAR dose-volume and combination of this function with our in-house developed treatment decision support system.Materials and methodsWe analysed the support vector machine and decision tree algorithm for predicting OAR complication level and toxicity in order to integrate this function into our in-house radiation treatment planning decision support system. A total of 12 TomoTherapyTM treatment plans for prostate cancer were established, and a hundred modelled plans were generated to analyse the toxicity prediction for bladder and rectum.ResultsThe toxicity prediction algorithm analysis showed 91·0% accuracy in the training process. A scatter plot for bladder and rectum was obtained by 100 modelled plans and classification result derived. OAR complication level was analysed and risk factor for 25% bladder and 50% rectum was detected by decision tree. Therefore, it was shown that complication prediction of patients using big data-based clinical information is possible.ConclusionWe verified the accuracy of the tested algorithm using prostate cancer cases. Side effects can be minimised by applying this predictive modelling algorithm with the planning decision support system for patient-specific radiotherapy planning.

scholarly journals Development of a frugal crop planning decision support system for subsistence farmers

2016 ◽  
Author(s):  
◽  
Adam Friedland
Keyword(s):  
Information System ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Structural Testing ◽  
Strategic Decisions ◽  
Subsistence Farmers ◽  
Crop Planning ◽  
Support Tool ◽  
Planning Decision

This dissertation reports on the original study that undertakes the development of a frugal information system to support subsistence farmers through the use of the Agricultural Production Systems Simulator (APSIM) as a support tool to assist them in optimal strategic decisions making. The field of agriculture is vast and in-depth and a number of critical factors like soil type, rainfall and temperature are involved that farmers have to take into account. Farmers persistently face the challenges of increasing and sustaining yields to meet with the populaces demand with often limited resources, which makes strategic decisions on what to plant, when to plant, where to plant and how to plant in a particular season imperative. The way in which this study attempts to solve this agricultural decision making problem is with the use of the APSIM. This technology platform provides an advanced simulation of agricultural systems that can enable subsistence farmers to simulate a number of variables ranging from plant types, soil, climate and even management interactions. This research presents a frugal web-based crop planning decision support system that subsistence farmers can take advantage with the use of the APSIM. The APSIM platform was used to run simulations for various regions with the results containing the expected level of success along with other useful information for a specified crop in the vicinity, using state of the art software platforms and tools ranging from Google Maps application programming interfaces, Microsoft’s model view controller framework, JavaScript and others. The validity of this system was tested through a number of design science methods including structural testing and illustrative scenarios, show capability of the information system. The results obtained from this evaluation show a small but powerful tool that has the capability of servicing a multitude of farmers with crop management decisions.

An Operating Theater Planning Decision Support System

2013 ◽  
pp. 69-86 ◽  
Author(s):  
Carlos Gomes ◽  
Fabrício Sperandio ◽  
Arnon Peles ◽  
José Borges ◽  
António Carvalho Brito ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Public Hospitals ◽  
System Component ◽  
Operating Theater ◽  
Planning Processes ◽  
Planning Decision ◽  
And Performance ◽  
Main Components

The operating theater is the biggest hospital budget expenditure. The usage of surgery related resources and its intrinsic planning must be carefully devised in order to achieve better operational performance. However, from long to short term planning, the decision processes inherent to the operating theater are often the subject of empiricism. Moreover, the current hospital information systems available in Portuguese public hospitals lack a decision support system component, which could assist in achieving better planning solutions. This work reports the development of a centralized system for the operating theater planning to support decision-making tasks of surgeons, chief specialty managers, and hospital administration. Its main components concern surgery scheduling, operating theater’s resource allocation and performance measurement. The enhancement of the planning processes, the increase of policy compliance, and the overall performance of the operating theater compared to the former methodologies are also discussed.

A deep knowledge planning decision support system for aiding nuclear waste transportation decisions

1989 ◽  
Vol 13 (1) ◽  
pp. 15-27 ◽  
Author(s):  
William M. Bowen ◽  
Kenneth D. Weeks ◽  
Dinesh Batra ◽  
Timothy R. Hill
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Nuclear Waste ◽  
Support System ◽  
Deep Knowledge ◽  
Planning Decision

Towards a Planning Decision Support System for Low-Carbon Urban Development

2011 ◽  
pp. 423-438 ◽  
Author(s):  
Ivan Blecic ◽  
Arnaldo Cecchini ◽  
Matthias Falk ◽  
Serena Marras ◽  
David R. Pyles ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Urban Development ◽  
Support System ◽  
Low Carbon ◽  
Planning Decision
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