Sara Nasiri

Knowledge Management support for Quality Management to achieve higher customer satisfaction

As a Quality Management society transforms into a more knowledge and learned based society, it requires enhancement and improvement of strategies, systems and techniques towards meeting new expectations and demands. The importance of knowledge continues to grow to the spread of global networks, accelerated product cycles and changing market conditions. In this era; a progressive enterprise should strive to adapt itself successfully to new management skills, principles, abilities and higher levels of competency. Also customer demands and their levels of satisfaction are determined by new factors. In this paper, we surveyed related aspects of Knowledge Management in order to be integrated in Quality Management. Finally we have proposed a model of Knowledge Management approaches for supporting Quality Management to achieve higher customer satisfaction. It has been revealed that Knowledge Management brings and sustains advantages to fulfill customer demands by creating and supporting beneficial features through launching of appropriate Knowledge Management processes.

Improving CBR adaptation for recommendation of associated references in a knowledge-based learning assistant system

Abstract Case adaptation is a challenging phase of case-based reasoning (CBR) for recommendation of a matched case solution. Our proposed knowledge-based recommendation system analyzes the combination of visual and textual information in CBR medical system. In this paper a case-based reasoner uses medical expressions in a textual analysis to create word association profiles. Case-based Learning Assistant System (DePicT CLASS) finds significant references and learning materials by utilizing profile of words associations according to the problem description. This research proposes a new adaptation mechanism based on substitution, abstraction, and compositional method for collaborative recommendation in medical vocational educational training. The DePicT CLASS adaptation mechanism has a combination of value comparison based on requested word association profiles and manual adaptation based on user collaborative recommendation. In the adaptation process of the system, attract rate and adapt rate are defined and utilized for evaluating the adaptation results. Therefore, recommendation is a combination of references and learning materials with highest valued keyword association strength from the most similar cases.

Toward an integrated e-health based on acquired healthcare knowledge

In order to have an integrated knowledge based e-health, several tools are used. Some of them make knowledge accessible to users and support users in the exchange of knowledge (e.g. knowledge portals, applications). In this way through integrating knowledge, extraction of the knowledge from different sources and analyzes it in a knowledge-based way along with interaction of stakeholders and domain experts, leads to have a better care documentation and also a better communication between them.

Dynamics of knowledge assets and change management perspectives

Change Management (CM) is the major challenge of the strategic management particularly due to dynamics of knowledge assets (i.e. Temporal knowledge transformation) and also inadequate or insufficient use of knowledge, competencies and human creativities. In this context, CM needs to utilize Knowledge Management (KM) to guarantee successful implementation of the change and also to sustain long-term organizational advantages (e.g. Time to market and Return on Investment). Such co-operation needs to comprehensively consider internal factors to organizational success as well as external (e.g. Customers). Moreover measuring and evaluating the co-operation foreground the essence of integrating feedback loop into the framework to empower CM and assure the success of KM activities. In this paper, a formerly developed model, IQMP, is customized and adapted to support CM. The IQMP provides a comprehensive framework to deploy Performance Quality Indicators (PQIs) and a knowledge based analysis of feedback. Finally the paper discusses conception and potential application of the inherited model, Dynamic Knowledge Assets Management (DKAM).

Detect and Predict Melanoma Utilizing TCBR and Classification of Skin Lesions in a Learning Assistant System

In this paper, case-based reasoning is used as a problem-solving method in the development of DePicT Melanoma CLASS. It is a textual case-based system to detect and predict melanoma utilizing text information and image classification. Each case contains disease description and possible recommendation as references (images or texts). Case description has an image gallery and a word association profile which is the association strengths between the stages/types of melanoma and its symptoms and characteristics (keywords from text references). Therefore, in the retrieval and reuse process, first, requested problem which is as a new incoming case have to be retrieved from all collected cases, then, the solution of the most similar case is selected and recommended to users. In this paper support vector machine (SVM) and k-nearest neighbor (k-NN) classifiers are also used with the extracted features of skin lesions. A region growing method is applied by initialization of seed points for the segmentation. DePicT Melanoma CLASS is tested on sample texts and 400 images from ISIC archive dataset including two classes of Melanoma and it achieves 63% accuracy for the overall system.

A Prototype of Case-Based Skin Cancer Detector for Android Phones Based on DePicT Concept: CBMelanom

The purpose of this research is to develop the case-based system for detecting the skin cancer by utilizing the information retrieved from users. Conversational case-based reasoning guides users to describe their problem through the question-dialog procedure. DePicT is a knowledge based approach to Detect and Predict diseases using image classification and Text Information from patient health records. It utilizes graphical and textual data sources with a case-based reasoning recommendation. Case-based Melanom (CBMelanom) system is utilized DePicT concept in this paper to interact with users in order to capture their skin problems in a conversation (question-dialog) and to recommend them the related solution.

Package Insert Leaflet Analysis and Improvement to Reduce Patient Risk Factors: A Pharmacovigilance Approach in Computer Science

Current package inserts for medicines are confusing for many patients and can lead to non-compliance. To combat this problem, a readability assistance system has been designed to analyze and improve leaflets to reduce the risks for patients, such as incorrect use of medication. This assistance system is divided into 5 levels: pharmaceutical readability index, graphical package insert leaflet overview, paragraph analysis, sentence analysis and recommendation of sentence rearrangement. The assistance system is designed only as a guide for the person in charge of the Patient Information Leaflet (PIL) to guard against possible misunderstanding of the PIL. The final decision is always with the person in charge for the correctness of the wording. In the future it is planned to adapt the assistance system to other types of leaflets.