• Biomolecules & Therapeutics
• /
• 제19권4호
• /
• pp.371-389
• /
• 2011

A new strategy for cancer therapy has emerged during the past decade based on molecular targets that are less likely to be essential in all cells in the body, therefore confer a wider therapeutic window than traditional cytotoxic drugs which mechanism of action is to inhibit essential cellular functions. Exceptional heterogeneity and adaptability of cancer impose significant challenges in oncology drug discovery, and the concept of complex tumor biology has led the framework of developing many anticancer therapeutics. Protein kinases are the most pursued targets in oncology drug discovery. To date, 12 small molecule kinase inhibitors have been approved by US Food and Drug Administration, and many more are in clinical development. With demonstrated clinical efficacy of bortezomib, ubiquitin proteasome and ubiquitin-like protein conjugation systems are also emerging as new therapeutic targets in cancer therapy. In this review, strategies of targeted cancer therapies with inhibitors of kinases and proteasome systems are discussed. Combinational cancer therapy to overcome drug resistance and to achieve greater treatment benefit through the additive or synergistic effects of each individual agent is also discussed. Finally, the opportunities in the future cancer therapy with molecularly targeted anticancer therapeutics are addressed.

• 한국멀티미디어학회논문지
• /
• 제22권2호
• /
• pp.322-333
• /
• 2019

After the launch of smart phones, various miniaturized smart devices such as wearable and IOT devices have deeply embedded in human life, and have created a technology-oriented society. In this technology-oriented society, technology development itself is important, however it seems more important to utilize existing technology appropriately and deliver effectively to human life. As the computer became personalized after the appearance of PC, human-centered computing such as HCI and UCD had begun to appear. However, most of the researches focused on technology that made human being convenient to interact with computer such as computer systems design and UX development. In the technology-oriented society, it seems more urgent to apply existing technology to human life. In this paper, we propose a methodology, 'Digital Leveraging' which guides how to effectively apply technology to human life. Digital Leveraging is the way of convergence between technology and humanities.

• Toxicological Research
• /
• 제35권4호
• /
• pp.319-330
• /
• 2019

Adverse drug reactions (ADRs) constitute key factors in determining successful medication therapy in clinical situations. Integrative analysis of electronic medical record (EMR) data and use of proper analytical tools are requisite to conduct retrospective surveillance of clinical decisions on medications. Thus, we suggest that electronic medical recording and human genetic databases are considered together in future directions of pharmacovigilance. We analyzed EMR-based ADR studies indexed on PubMed during the period from 2005 to 2017 and retrospectively acquired 1161 (29.6%) articles describing drug-induced adverse reactions (e.g., liver, kidney, nervous system, immune system, and inflammatory responses). Of them, only 102 (8.79%) articles contained useful information to detect or predict ADRs in the context of clinical medication alerts. Since insufficiency of EMR datasets and their improper analyses may provide false warnings on clinical decision, efforts should be made to overcome possible problems on data-mining, analysis, statistics, and standardization. Thus, we address the characteristics and limitations on retrospective EMR database studies in hospital settings. Since gene expression and genetic variations among individuals impact ADRs, pharmacokinetics, and pharmacodynamics, appropriate paths for pharmacovigilance may be optimized using suitable databases available in public domain (e.g., genome-wide association studies (GWAS), non-coding RNAs, microRNAs, proteomics, and genetic variations), novel targets, and biomarkers. These efforts with new validated biomarker analyses would be of help to repurpose clinical and translational research infrastructure and ultimately future personalized therapy considering ADRs.

• 한국IT서비스학회지
• /
• 제20권3호
• /
• pp.57-73
• /
• 2021

Recently, online job websites have been activated as unemployment problems have emerged as social problems and demand for job openings has increased. However, while the online job platform market is growing, users have difficulty choosing their jobs. When users apply for a job on online job websites, they check various information such as job contents and recruitment conditions to understand the details of the job. When users choose a job, they focus on various details related to the job rather than simply viewing and supporting the job title. However, existing online job websites usually recommend jobs using only quantitative preference information such as ratings. However, if recommendation services are provided using only quantitative information, the recommendation performance is constantly deteriorating. Therefore, job recommendation services should provide personalized services using various information about the job. This study proposes a recommended methodology that improves recommendation performance by elaborating on qualitative preference information, such as details about the job. To this end, this study performs a topic modeling analysis on the job content of the user profile. Also, we apply LDA techniques to explore topics from job content and extract qualitative preferences. Experiments show that the proposed recommendation methodology has better recommendation performance compared to the traditional recommendation methodology.

• 디지털융복합연구
• /
• 제18권12호
• /
• pp.97-103
• /
• 2020

제안한 시스템은 AI 체력측정 파트와 AI 체력관리 파트 2가지 부분이 연계성을 가지고 구성되어 있다. AI 체력측정 파트에서 딥러닝 기반의 포즈인식을 통해 체력측정에 대한 가이드와 측정값의 정확한 연산을 수행한다. 이 측정값을 기반으로 AI 체력관리 파트에서는 개인 맞춤형 운동프로그램을 설계해 전용 스마트 어플리케이션에 제공한다. 측정자세 가이드를 위해 웹캠을 통해 측정대상자의 자세를 촬영해 골격선을 추출한다. 다음으로 학습된 준비자세의 골격선과 추출된 골격선을 비교해 정상 유무를 판단하고, 정상자세 유지를 위한 음성안내를 실시한다.

• Physical Therapy Rehabilitation Science
• /
• 제12권3호
• /
• pp.251-258
• /
• 2023

Objective: The practice of breathing exercises involves altering the depth and frequency of respiration. Strengthening respiratory muscles plays a crucial role in maintaining overall health and well-being. The efficiency of the respiratory system affects not only physical activity but also various physiological processes including cardiovascular health, lung function, and cognitive abilities. The study evaluated the reliability of the developed device for inspiratory/expiratory training using pressure sensors and Bluetooth connectivity with a smartphone application. Design: Design & development research Methods: The research methodology involved connecting a custom-made respiratory sensor to an IMT-PEP BIC Breath device. Various pressure conditions were measured, and statistical analyses were performed to assess reliability and consistency. Results showed high Intraclass Coefficient Correlation (ICC) values for both inspiratory and expiratory pressures, indicating strong test-retest reliability. The device was designed for ease of use and wireless monitoring through a smartphone app. Results: This study conducted at expiratory pressure confirmed the proper operation of the IMT/PEP breathing trainer at the specified pressure setting in the product. The pressure sensor demonstrated high test-retest reliability with an ICC value of 0.999 for both expiratory and inspiratory pressure measurements. Conclusions: The developed respiratory training device measured and monitored inspiratory and expiratory pressures, demonstrating its reliability for respiratory training. The system could be utilized to record training frequency and intensity, providing potential benefits for patients requiring respiratory interventions. Further research is needed to assess the full potential of the device in diverse populations and applications.

• Journal of Information Technology Applications and Management
• /
• 제31권3호
• /
• pp.149-163
• /
• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• 한국전자통신학회논문지
• /
• 제19권3호
• /
• pp.633-640
• /
• 2024

이 연구는 헬스케어 분야에서 활용 가능한 AI 기반의 3D 체형 모델링 기술을 개발하고, 이를 통해 사용자의 체형 변화와 건강 상태를 모니터링 할 수 있는 시스템을 제안한다. 사이즈코리아의 데이터를 활용하여 2D 이미지로부터 3D 체형 이미지를 생성하는 모델을 개발하고, 다양한 모델을 비교하여 가장 성능이 우수한 모델을 선정하였다. 최종적으로, 개발된 기술을 통해 개인 맞춤형 건강 관리, 운동 추천, 식단 제안 등의 시스템 프로세스를 제안함으로써 질병 예방 및 건강 증진에 기여하고자 하였다.

• Mass Spectrometry Letters
• /
• 제15권2호
• /
• pp.69 -78
• /
• 2024

The advancement of high-throughput omics technologies and systems biology is essential for understanding complex biological mechanisms and diseases. The integration of proteomics and metabolomics provides comprehensive insights into cellular functions and disease pathology, driven by developments in mass spectrometry (MS) technologies, including electrospray ionization (ESI). These advancements are crucial for interpreting biological systems effectively. However, integrating these technologies poses challenges. Compared to genomic, proteomics and metabolomics have limitations in throughput, and data integration. This review examines developments in MS equipped electrospray ionization (ESI), and their importance in the effective interpretation of biological mechanisms. The review also discusses developments in sample preparation, such as Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX), analytical techniques, and data analysis, highlighting the application of these technologies in the study of cancer or Huntington's disease, underscoring the potential for personalized medicine and diagnostic accuracy. Efforts by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and integrative data analysis methods such as O2PLS and OnPLS extract statistical similarities between metabolomic and proteomic data. System modeling techniques that mathematically explain and predict system responses are also covered. This practical application also shows significant improvements in cancer research, diagnostic accuracy and therapeutic targeting for diseases like pancreatic ductal adenocarcinoma, non-small cell lung cancer, and Huntington's disease. These approaches enable researchers to develop standardized protocols, and interoperable software and databases, expanding multi-omics research application in clinical practice.

• 인터넷정보학회논문지
• /
• 제17권1호
• /
• pp.15-21
• /
• 2016

최근 정부는 창조경제라는 패러다임에 따라 다양한 분야의 공공데이터를 개방하고 여러 종류의 대국민 서비스를 구축하는 등 공공데이터 활용을 통한 가치창출에 역점을 두고 있다. 본 논문에서는 여행에 관한 공공데이터와 사용자 정보를 융합하여 사용자에게 맞춤형 여행 정보를 추천하는 시스템을 구현하였다. 본 시스템에서는 사례기반추론(CBR) 방식을 이용하여 사용자별 맞춤형 정보 추천이 가능하도록 하였다. 본 시스템은 사용자 중심의 여행 정보를 제공한다는 측면에서 기존의 여행 시스템들과 차별화된다고 할 수 있으며, 턴키(Turn-key) 방식의 콘텐츠 제공으로 사용자의 편의성을 극대화할 수 있는 유용한 도구로 활용될 수 있을 것으로 판단된다. 본 연구가 공공데이터의 성공적인 활용 사례가 되기를 기대한다.