• Journal of Gastric Cancer
• /
• v.13 no.3
• /
• pp.129-135
• /
• 2013

Gastric cancer is the second leading cause of cancer-related deaths worldwide. In advanced and metastatic gastric cancer, the conventional chemotherapy with limited efficacy shows an overall survival period of about 10 months. Patient specific and effective treatments known as personalized cancer therapy is of significant importance. Advances in high-throughput technologies such as microarray and next generation sequencing for genes, protein expression profiles and oncogenic signaling pathways have reinforced the discovery of treatment targets and personalized treatments. However, there are numerous challenges from cancer target discoveries to practical clinical benefits. Although there is a flood of biomarkers and target agents, only a minority of patients are tested and treated accordingly. Numerous molecular target agents have been under investigation for gastric cancer. Currently, targets for gastric cancer include the epidermal growth factor receptor family, mesenchymal-epithelial transition factor axis, and the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathways. Deeper insights of molecular characteristics for gastric cancer has enabled the molecular classification of gastric cancer, the diagnosis of gastric cancer, the prediction of prognosis, the recognition of gastric cancer driver genes, and the discovery of potential therapeutic targets. Not only have we deeper insights for the molecular diversity of gastric cancer, but we have also prospected both affirmative potentials and hurdles to molecular diagnostics. New paradigm of transdisciplinary team science, which is composed of innovative explorations and clinical investigations of oncologists, geneticists, pathologists, biologists, and bio-informaticians, is mandatory to recognize personalized target therapy.

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

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

• Journal of Korea Multimedia Society
• /
• v.8 no.6
• /
• pp.814-826
• /
• 2005

The user-centric broadcasting environment includes the agent system and personalized broadcasting services for user-adaptive TV watching. In this paper, we propose broadcasting environment consisting of personalized broadcasting services and a multi-agent broadcasting system for the services. The proposed system employs the intelligent agent technology of the Foundation for Intelligent Physical Agents (FIPA) as well as metadata technology of MPEG-7 and TV-Anytime Forum (TVAF). To verify the usefulness of the proposed environment, we implemented a test-bed and demonstrated the proposed agent system with three services including intelligent user-information management service, information mobility service, and content retrieval service.

• Asia pacific journal of information systems
• /
• v.15 no.3
• /
• pp.223-241
• /
• 2005

In spite of the rapid growth of mobile multimedia contents market, most of the customers experience inconvenience, lengthy search processes and frustration in searching for the specific multimedia contents they want. These difficulties are attributable to the current mobile Internet service method based on inefficient sequential search. To overcome these difficulties, this paper proposes a MOBIIe COntents Recommender System for Movie(MOBICORS-Movie), which is designed to reduce customers' search efforts in finding desired movies on the mobile Internet. MOBICORS-Movie consists of three agents: CF(Collaborative Filtering), CBIR(Content-Based Information Retrieval) and RF(Relevance Feedback). These agents collaborate each other to support a customer in finding a desired movie by generating personalized recommendations of movies. To verify the performance of MOBICORS-Movie, the simulation-based experiments were conducted. The results from this experiments show that MOBICORS-Movie significantly reduces the customer's search effort and can be a realistic solution for movie recommendation in the mobile Internet environment.

• Journal of Pharmaceutical Investigation
• /
• v.41 no.2
• /
• pp.59-65
• /
• 2011

Nanotechnology for cancer therapy is playing a pivotal role in dramatically improving current approaches to cancer detection, diagnosis, and therapy while reducing toxic side effects associated with previous cancer therapy. A widespread understanding of these new technologies will lead to develop the more refined design of optimized nanoparticles with improved selectivity, efficacy and safety in the clinical practice of oncology. This review provides an integrated overview of applications and advances of nanotechnology in cancer therapy, based on molecular diagnostics, treatment, monitoring, target drug delivery, approved nanoparticle-based chemotherapeutic agents, and current clinical trials in the development of nanomedicine and ultimately personalized medicine.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.8
• /
• pp.1109-1116
• /
• 2001

This paper describes a mechanism and its aspects for monitoring user actions and behaviors on the web operated under the layered architecture that utilizes intelligent agents, and by which personalized information services, for instance one-to-one marketing, is easily facilitated and developed. Intelligent agent is one of techniques which enables to automate the whole process for providing personalized services that includes monitoring, logging a user actions and analyzing behaviors based on his or her profiles, and then selecting, organizing customizable contents which are at last delivered to the users browser or mail box also by intelligent agents. Monitoring technologies can utilize to help better construct the process in providing personalized services in that those services require intelligence in operating. As a result, implementing effective personalized services, however, depends on how well to define various users interests and needs, and how correctly to detect and log the actions when hey are done by users.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.2
• /
• pp.215-221
• /
• 2003

Generally, we want to be searched the newest as well as some appropriate personalized information from the internet resources. However, it is a complex and repeated procedure to search some appropriate information. Moreover, because the user's interests are changed as time goes, the real time modeling of a user's interests should be necessary. In this paper, I propose PREA system that can search and filter documents that users are interested from the World Wide Web. And then it constructs the user's interest model by a modified spreading neural network. Based on this network, PREA can easily produce some queries to search web documents, and it ranks them. The conventional spreading neural network does not have a visualization function, so that the users could not know how to be configured his or her interest model by the network. To solve this problem, PREA gives a visualization function being shown how to be made his interest user model to many users.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1160-1163
• /
• 2021

DOOH(Degital Out of Home) advertisement market is developing steadily, and the case of use is also increasing, In advertisement market, personalized services is actively being provided with technological development. On the other hand, personalized services are difficult to be provided in DOOH and are p rovided by only personal information, not feelings. This study aims to construct personalized DOOH se rvices by using AI facial expression recognition and suggesting a solution optimized for interaction bet ween user and services by providing healing and advertisement.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.533-540
• /
• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.