Personalized medicine support system : resolving conflict in allocation to risk groups and predicting patient molecular response to targeted therapy

Treatment management in cancer patients is largely based on the use of a standardized set of predictive and prognostic factors. The former are used to evaluate specific clinical interventions, and they can be useful for selecting treatments because they directly predict the response to a treatment. The latter are used to evaluate a patient’s overall outcomes, and can be used to identify the risks or recurrence of a disease. Current intelligent systems can be a solution for transferring advancements in molecular biology into practice, especially for predicting the molecular response to molecular targeted therapy and the prognosis of risk groups in cancer medicine. This framework primarily focuses on the importance of integrating domain knowledge in predictive and prognostic models for personalized treatment. Our personalized medicine support system provides the needed support in complex decisions and can be incorporated into a treatment guide for selecting molecular targeted therapies.Haneen Banjar, David Adelson, Fred Brown, and Tamara Leclerc

Conflict resolution for product performance requirements based on propagation analysis in the extension theory

Traditional product data mining methods are mainly focused on the static data. Performance requirements are generally met as possible by finding some cases and changing their structures. However, when one is satisfied with the structures changed, the other effects are not taken into account by analyzing the correlations; that is, design conflicts are not identified and resolved. An approach to resolving the conflict problems is proposed based on propagation analysis in Extension Theory. Firstly, the extension distance is improved to better fit evaluating the similarity among cases, then, a case retrieval method is developed. Secondly, the transformations that can be made on selected cases are formulated by understanding the conflict natures in the different performance requirements, which leads to the extension transformation strategy development for coordinating conflicts using propagation analysis. Thirdly, the effects and levels of propagation are determined by analyzing the performance values before and after the transformations, thus the co-existing conflict coordination strategy of multiple performances is developed. The method has been implemented in a working prototype system for supporting decision-making. And it has been demonstrated the feasible and effective through resolving the conflicts of noise, exhaust, weight and intake pressure for the screw air compressor performance design

Knowledge-based inventive conceptual design

Conceptual design is the first phase of the design process. Most basic functions of a new product and the solutions for solving design problems are generated in this critical phase, which will affect the attributes in the later detailed design process. Conceptual design, especially the process of concept generation, is an innovation process that is achieved by human intelligence. The intuition and experience of designers play a significant role during the design process which is hard to be replaced by computer-aided tools or artificial intelligence technology. TR1Z is an inventive problem-solving tool to help people improve creativity. It is applied in this work to generate creative design concepts. The TRIZ inventive principles are extended by integrating other TRIZ tools and TRIZ-derived tools. These principles are also restructured by the inspiration of I-Ching. The Behaviour-Entity representation of inventive principles enables the generation of new and innovative solutions based on TRIZ. The TRIZ Contradiction Matrix (CM) and inventive principles are then used to develop the TRIZ-based concept generation approach by adding constraints to the standard Behaviour-Entity representation of TRIZ. This approach is developed to retrieve modified TRIZ inventive principles and to generate new solutions by re-organising the BEC (Behaviour-Entity-Constraint) representation of principles according to the conflicting design requirements. Finally, a negotiation-based approach is integrated with an existing no-compromise approach to develop a knowledge-based system for automatically detecting and resolving conflicts. The recommendation is given as an output arranged by weight to help the designer improve creativity and efficiency for concept generation and conflict resolution in conceptual design. The approach is implemented by using a rule-based language, JESS. A case study of aircraft fuselage layout design is presented to demonstrate the benefits of using this conflict resolution system.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Knowledge-based inventive conceptual design

Conceptual design is the first phase of the design process. Most basic functions of a new product and the solutions for solving design problems are generated in this critical phase, which will affect the attributes in the later detailed design process. Conceptual design, especially the process of concept generation, is an innovation process that is achieved by human intelligence. The intuition and experience of designers play a significant role during the design process which is hard to be replaced by computer-aided tools or artificial intelligence technology. TR1Z is an inventive problem-solving tool to help people improve creativity. It is applied in this work to generate creative design concepts. The TRIZ inventive principles are extended by integrating other TRIZ tools and TRIZ-derived tools. These principles are also restructured by the inspiration of I-Ching. The Behaviour-Entity representation of inventive principles enables the generation of new and innovative solutions based on TRIZ. The TRIZ Contradiction Matrix (CM) and inventive principles are then used to develop the TRIZ-based concept generation approach by adding constraints to the standard Behaviour-Entity representation of TRIZ. This approach is developed to retrieve modified TRIZ inventive principles and to generate new solutions by re-organising the BEC (Behaviour-Entity-Constraint) representation of principles according to the conflicting design requirements. Finally, a negotiation-based approach is integrated with an existing no-compromise approach to develop a knowledge-based system for automatically detecting and resolving conflicts. The recommendation is given as an output arranged by weight to help the designer improve creativity and efficiency for concept generation and conflict resolution in conceptual design. The approach is implemented by using a rule-based language, JESS. A case study of aircraft fuselage layout design is presented to demonstrate the benefits of using this conflict resolution system

Preventing and resolving design conflicts for a collaborative convergence in distributed set-based design

En conception distribuée, dans la phase du dimensionnement du produit, des incohérences peuvent émerger entre les objectifs de conception et entre les procédures de travail des sous-systèmes hétérogènes. Dans cette phase, les acteurs de conception doivent collaborer d une manière concourante, car leurs tâches sont reliées les unes aux autres par les couplages de dimensionnement entre leurs sous-problèmes. Les incohérences peuvent provoquer des conflits de conception en raison de ces couplages. La question est de savoir comment obtenir une convergence collaborative pour satisfaire les objectifs globaux et individuels des acteurs de conception lorsque ces acteurs prennent des décisions de conception sous incertitude. L'objectif de cette thèse est de proposer un modèle pour empêcher et résoudre les conflits de conception, tout en surmontant le problème de l'incertitude de la conception avec l'approche de conception basée sur les ensembles (SBD). Pour cela, les attitudes de conception sont modélisées avec le paradigme Croyances-Désirs-Intentions afin d'explorer les incohérences et gérer les conflits dans les processus de conception. L'approche ascendante conventionnelle est ainsi étendue grâce à des techniques de modélisation multi-agents. Dans cette approche, les agents de conception peuvent fixer des exigences directement sur leurs indicateurs de bien-être . Ces indicateurs représentent la manière dont leurs objectifs de conception sont susceptibles d'être satisfaits à un moment donné du processus. Des simulations de Monte Carlo sont effectuées pour évaluer la performance de cette approche, offrant une variété d'attitudes de l'agent. Par rapport aux approches classiques de conception ascendante et descendante, les résultats révèlent moins de conflits de conception et une intensité des conflits réduite. Les techniques de problème de satisfaction de contraintes (CSP) et les attitudes de conception sont appliquées pour détecter et justifier des conflits de conception entre les agents hétérogènes. Une nouvelle forme du modèle Cooperative CSP (CoCSP) est ainsi mise au point afin de résoudre les conflits de conception en détectant le compromis entre les contraintes. Le système de résolution des conflits peut être adopté grâce à différentes stratégies proposées qui prennent en compte l'architecture de solidarité des agents. Les résultats des simulations montrent que l'intensité des conflits en conception distribuée est réduite par la promotion de la solidarité qui déclenche une aide aux agents en souffrance.In the product dimensioning phase of a distributed design, inconsistencies can emerge among design objectives as well as among working procedures of heterogeneous subsystems. In this phase, design actors which compose subsystems must collaborate concurrently, since their works are linked to each other through dimensioning couplings among their sub-problems. Inconsistencies through these couplings yield thus to design conflicts. The issue is how to obtain a collaborative convergence to satisfy the global and individual objectives of design actors when making design decisions under uncertainty. The objective of this dissertation is to propose a model for preventing and resolving design conflicts in order to obtain a collaborative convergence, while overcoming the design uncertainty through Set-based Design (SBD). Design attitudes are modeled with Belief-Desire-Intention paradigm to explore inconsistencies and manage conflicts in design processes. The conventional bottom-up approach is thus extended through agent-based attitude modeling techniques. In this approach, design agents can set requirements directly on their wellbeing values that represent how their design targets are likely to be met at a given moment of the design process. Monte Carlo simulations are performed to evaluate the performance of this approach, providing a variety of agent attitudes. Compared to conventional bottom-up and top-down design approaches, the results reveal a fewer number of design conflicts and a reduced aggregated conflict intensity. Constraint satisfaction problem (CSP) techniques and design attitudes are both applied to detect and justify design conflicts of heterogeneous design agents. A novel cooperative CSP (CoCSP) is developed in order to resolve design conflicts through compromising constraint restriction. The conflict resolution system can be adopted for different proposed strategies which take into account the solidarity architecture of design agents. The simulation results show that while promoting solidarity in distributed design by helping agents that suffer, the conflict intensity is reduced, and better design results are obtained.CHATENAY MALABRY-Ecole centrale (920192301) / SudocSudocFranceF

Investigation of a design performance measurement tool for improving collaborative design during a design process

With rapid growth of global competition, the design process is becoming more and more complex due largely to cross-functional team collaboration, dynamic design processes, and unpredictable design outcomes. Thus, it is becoming progressively more difficult to support and improve design activities effectively during a design process, especially from a collaboration perspective. Although a great deal of research pays attention to the support and improvement of design collaboration from multi-perspectives, little research attention has been directed at improving collaborative design by a performance measurement approach. In addition, many studies have demonstrated that performance measurement can improve design effectiveness significantly. Therefore, this PhD research focused on investigating ‘How to improve collaborative design via a performance measurement approach?’ A Design Performance Measurement (DPM) tool, which enables design managers and designers to measure and improve design collaboration during a design process, has been developed. The DPM tool can support the design team members in learning from performance measurement and, in turn, drive the design project towards the achievement of strategic objectives, and goes beyond monitoring and controlling them during the project development process. It is, thus, a motivating tool as well as a support tool for the development of product design. The proposed DPM tool has three novel components: • A DPM operation model, which integrates a hierarchical design team structure with a multi-feedback interaction performance measurement approach to support DPM operation in a design project team. • A DPM matrix, which enables collaborative design performance to be measured during a design process. • A DPM weighting application model to improve flexibility of the DPM tool by integrating DPM with the design project’s strategies, stage-based design objectives, and design staff’s job focuses and responsibilities. This tool has been positively evaluated through two industry case studies and a software-based simulation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Personalized Medicine Support System for Chronic Myeloid Leukemia Patients

Personalized medicine offers the most effective treatment protocols to the individual Chronic Myeloid Leukemia (CML) patients. Understanding the molecular biology that causes CML assists in providing efficient treatment. After the identification of an activated tyrosine kinase BCR-ABL1 as the causative lesion in CML, the first-generation Tyrosine Kinase inhibitors (TKI) imatinib (Glivec®), were developed to inhibit BCR-ABL1 activity and approved as a treatment for CML. Despite the remarkable increase in the survival rate of CML patients treated with imatinib, some patients discontinued imatinib therapy due to intolerance, resistance or progression. These patients may benefit from the use of secondgeneration TKIs, such as nilotinib (Tasigna®) and dasatinib (Sprycel®). All three of these TKIs are currently approved for use as frontline treatments. Prognostic scores and molecularbased predictive assays are used to personalize the care of CML patients by allocating risk groups and predicting responses to therapy. Although prognostic scores remain in use today, they are often inadequate for three main reasons. Firstly, since each prognostic score may generate conflicting prognoses for the risk index and it can be difficult to know how to treat patients with conflicting prognoses. Secondly, since prognostic score systems are developed over time, patients can benefit from newly developed systems and information. Finally, the earlier scores use mostly clinically oriented factors instead of those directly related to genetic or molecular indicators. As the current CML treatment guidelines recommend the use of TKI therapy, a new tool that combines the well-known, molecular-based predictive assays to predict molecular response to TKI has not been considered in previous research. Therefore, the main goal of this research is to improve the ability to manage CML disease in individual CML patients and support CML physicians in TKI therapy treatment selection by correctly allocating patients to risk groups and predicting their molecular response to the selected treatment. To achieve this objective, the research detailed here focuses on developing a prognostic model and a predictive model for use as a personalized medicine support system. The system will be considered a knowledge-based clinical decision support system that includes two models embedded in a decision tree. The main idea is to classify patients into risk groups using the prognostic model, while the patients identified as part of the high-risk group should be considered for more aggressive imatinib therapy or switched to secondgeneration TKI with close monitoring. For patients assigned to the low-risk group to imatinib should be predicted using the predictive model. The outcomes should be evaluated by comparing the results of these models with the actual responses to imatinib in patients from a previous medical trial and from patients admitted to hospitals. Validating such a predictive system could greatly assist clinicians in clinical decision-making geared toward individualized medicine. Our findings suggest that the system provides treatment recommendations that could help improve overall healthcare for CML patients. Study limitations included the impact of diversity on human expertise, changing predictive factors, population and prediction endpoints, the impact of time and patient personal issues. Further intensive research activities based on the development of a new predictive model and the method for selecting predictive factors and validation can be expanded to other health organizations and the development of models to predict responses to other TKIs.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 201