• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1693-1698
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• 2015

The heterogeneous nature of lung cancer has become increasingly apparent since introduction of molecular classification. In general, advanced lung cancer is an aggressive malignancy with a poor prognosis. Activating alterations in several potential driver oncogenic genes have been identified, including EGFR, ROS1 and ALK and understanding of their molecular mechanisms underlying development, progression, and survival of lung cancer has led to the design of personalized treatments that have produced superior clinical outcomes in tumours harbouring these mutations. In light of the tsunami of new biomarkers and targeted agents, next generation sequencing testing strategies will be more appropriate in identifying the patients for each therapy and enabling personalized patients care. The challenge now is how best to interpret the results of these genomic tests, in the context of other clinical data, to optimize treatment choices. In genomic era of cancer treatment, the traditional one-size-fits-all paradigm is being replaced with more effective, personalized oncologic care. This review provides an overview of lung cancer genomics and personalized treatment.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.233-241
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• 2007

In an ubiquitous environment, for controlling user access according to environment of users, a number of access control models enforcing dynamic environment of users have been proposed. However, they do not support personalized environments of each user and have a run-time overhead of searching active roles. In this paper, we propose a new model, PE-RBAC, that extends the RBAC architecture by addition of a personalized environment component as a constraint to accommodate dynamic and mobile users. In this model, a dynamic role activation is presented by using a new role-to-environment structure instead of the conventional role hierarchy, which makes it efficient to find the active roles according to a user's personalized environment.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.427-433
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• 2024

This study aims to develop a personalized music digital therapeutic based on MBTI personality types and apply it to depression treatment. In the data collection stage, participants' MBTI personality types and music preferences were surveyed to build a database, which was then preprocessed as input data for the KNN model. The KNN model calculates the distance between personality types using Euclidean distance and recommends music suitable for the user's MBTI type based on the nearest K neighbors' data. The developed system was tested with new participants, and the system and algorithm were improved based on user feedback. In the final validation stage, the system's effectiveness in alleviating depression was evaluated. The results showed that the MBTI personality type-based music recommendation system provides a personalized music therapy experience, positively impacting emotional stability and stress reduction. This study suggests the potential of nonpharmacological treatments and demonstrates that a personalized treatment experience can offer more effective and safer methods for treating depression.

• Journal of Digital Contents Society
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• v.2 no.2
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• pp.117-127
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• 2001

Since the number of e-malls is increased by the rapidly Progress of internet, most e-malls are trying to increase customers' interests by providing personalized services. To Provide this service for CRM, the e-mall must use the personalized rules calculated from customer transaction database. The more filtered transaction data are, the more the e-mall services efficiently and exactly to customer's need. The filtered transaction database is necessary to obtain the food personalized rules. In this paper we propose and develope a personalized e-mall with association rules based on view history of excellent customers who have good transaction data. Association rules based on view history of excellent customers reduce the access time and computing costs. The e-mall with them can provide personalized services more efficiently and exactly.

• BMB Reports
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• v.43 no.10
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• pp.643-648
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• 2010

Sir William Osler (1849-1919) recognized that "variability is the law of life, and as no two faces are the same, so no two bodies are alike, and no two individuals react alike and behave alike under the abnormal conditions we know as disease". Accordingly, the traditional methods of medicine are not always best for all patients. Over the last decade, the study of genomes and their derivatives (RNA, protein and metabolite) has rapidly advanced to the point that genomic research now serves as the basis for many medical decisions and public health initiatives. Genomic tools such as sequence variation, transcription and, more recently, personal genome sequencing enable the precise prediction and treatment of disease. At present, DNA-based risk assessment for common complex diseases, application of molecular signatures for cancer diagnosis and prognosis, genome-guided therapy, and dose selection of therapeutic drugs are the important issues in personalized medicine. In order to make personalized medicine effective, these genomic techniques must be standardized and integrated into health systems and clinical workflow. In addition, full application of personalized or genomic medicine requires dramatic changes in regulatory and reimbursement policies as well as legislative protection related to privacy. This review aims to provide a general overview of these topics in the field of personalized medicine.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.105-115
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• 2010

Search engines provide web documents that are related to user's query. However, using only the query terms that user provided, it is hard for search engines to know user's exact intention and provide the very matching web documents. To remedy this problem, search systems are needed to exploit personalized search technologies. In this paper, we propose not only a novel personalized query recommendation scheme based on folksonomy but also a new personalized search service architecture which reduces the risk of privacy violation while enabling search service providers to provide other various personalized services such as personalized advertisement.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• ETRI Journal
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• v.26 no.5
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• pp.452-466
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• 2004

As the number of broadcasting channels and programs increases rapidly, the importance of personalized service has been emphasized. In this paper, we propose a practical framework of metadata broadcasting to provide personalized service according to user preferences and various terminal/network conditions. First, we present an overall system architecture of a metadata broadcasting system and then propose several core technologies (particularly in the parts of metadata authoring, metadata encoding, and metadata-based personalized content consumption). For interoperability, the proposed solution is designed to be compliant with the relevant standards of the TV-Anytime Forum, MPEG-7 Systems, and MPEG-2 Systems. Considering a home network environment, we also propose a metadata-based content adaptation scheme. Each component technology has been implemented individually, integrated into an end-to-end prototype broadcasting system, and successfully tested with a set of personalized service scenarios that are also developed in this study.

• Journal of Distribution Science
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• v.22 no.2
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• pp.11-20
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• 2024

Purpose: The primary objective of this study is to investigate the impact of website quality on impulse buying of the online retailer, which is mediated by positive emotion and moderated by personalized advertising. Research design, data and methodology: The present study used a survey methodology conducted on many user's smartphones. The sample in this study included 409 college students in Indonesia. Purposive sampling was used as the sampling technique. Data was collected by distributing questionnaires to many respondents through the Google Documents online survey. Results: The findings derived from the application of structural equation modelling for data analysis show that 1). Website quality affects impulse buying and positive emotion, and 2). The impact of website quality on impulse buying was mediated by positive emotion and moderated by personalized advertising. Conclusions: The findings presented in this study has significant theoretical implications that contribute to the existing concept on the relationship between website quality, positive emotion, personalized advertising and impulse buying. The findings of the research possess managerial implications. It can be used can as a reference in determining website quality and the appropriate personalized advertising that increases online impulse buying at online retailer In Indonesia.

• Asia pacific journal of information systems
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• v.29 no.2
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• pp.203-216
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• 2019

There is an accuracy-diversity dilemma with personalized recommendation services. Some researchers believe that accurate recommendations might reinforce customer satisfaction. However, others claim that highly accurate recommendations and customer satisfaction are not always correlated. Thus, this study attempts to establish the causal factors that determine customer satisfaction with personalized recommendation services to reconcile these incompatible views. This paper employs statistical analyses of simulation to investigate an accuracy-diversity dilemma with personalized recommendation services. To this end, we develop a personalized recommendation system and measured accuracy, diversity, and customer satisfaction using a simulation method. The results show that accurate recommendations positively affected customer satisfaction, whereas diverse recommendations negatively affected customer satisfaction. Also, customer satisfaction was associated with the recommendation product size when neighborhood size was optimal in accuracy. Thus, these results offer insights into personalizing recommendation service providers. The providers must identify customers' preferences correctly and suggest more accurate recommendations. Furthermore, accuracy is not always improved as the number of product recommendation increases. Accordingly, providers must propose adequate number of product recommendation.