김종우 교수

In colorectal carcinogenesis, the unique molecular and genetic changes that occur within cells result in specific CRC phenotypes. The involvement of the long non-coding RNA, HOTAIR, in cancer development, progression, and metastasis is well established. Various studies have reported on the contribution of HOTAIR to cancer pathogenesis. Therefore, we selected four HOTAIR polymorphisms (rs7958904G>C, rs1899663G>T, rs4759314A>G, and rs920778T>C) to evaluate the association of each variant with CRC

Reinforcement learning (RL) can be used to obtain an approximate numerical solution to the Hamilton-Jacobi-Bellman (HJB) equation. Recent advances in machine learning community enable the use of deep neural networks (DNNs) to approximate high-dimensional nonlinear functions as those that occur in RL, accurately without any domain knowledge. In the standard RL setting, both system and cost structures are unknown, and the amount of data needed to obtain an accurate approximation can be impractical

다른 산업과 달리 병원/의료 산업에서는 건강 보험료 심사 평가라는 독특한 검증 과정이 필수적으로 있게 된다. 건강 보험료 심사 평가는 병원의 수익 문제 뿐 아니라 적정한 진료행위를 하는 병원이라는 이미지와도 맞물려 매우 중요한 분야이며, 특히 대형 종합병원일수록 이 부분에 많은 심사관련 인력들을 투입하여, 병원의 수익과 명예를 위해서 업무를 수행하고 있다. 본 논문은 이러한 건강보험료 청구 심사 과정에서, 사전에 수많은 진료 청구 건 중 심사 평가에서 삭감이 될 수 있는 진료 청구 건을 데이터 마이닝을 통해서 발견하여, 사전의 대비를 철저히 하고자 하는 한 국내 대형 종합병원의 사례를 소개하고자 한다. 데이터 마이닝을 적용함에 있어, 주요한 문제점 중 하나는 바로 지도학습 기법을 적용하기에 곤란한 데이터 불균형 문제가 발생하는 것이다. 이런 불균형 문제를 해소하고, 비교 조건 중에 가장 효율적인 삭감 예상 진료 건 탐지 모델을 만들어 내기 위하여, 데이터 불균형 문제의 기본 해법인

Collaborative filtering is one of popular techniques for personalized recommendation in e-commerce sites. An advantage of collaborative filtering is that the technique can work with sparse evaluation data to predict preference scores of new alternative contents or advertisements. There is, however, no in-depth study about the sparsity effect of customer's evaluation data to the performance of recommendation. In this study, we investigate the sparsity effect and hybrid usages of customers' evalua

Optimal scheduling of maintenance and improvement on the water main system is a substantial problem since it can greatly reduces the potential threat of failure and the expenses. The Markov decision process (MDP) based methodology to find the optimal schedule which minimizes the cost is proposed. Since it needs the information about the current state of pipe, cost, and deterioration model, the definition and the usage of auxiliary information are also presented. The objective function and detail

Optimal experimental design for parameter precision attempts to maximize the information content in experimental data for a most effective identification of parametric model. With the recent developments in miniaturization and parallelization of cultivation platforms for high-throughput screening of optimal growth conditions massive amounts of informative data can be generated with few experiments. Increasing the quantity of the data means to increase the number of parameters and experimental de

OBJECTIVE: To quantify magnetic resonance imaging (MRI) findings of congenital muscular torticollis (CMT) and to demonstrate the usefulness of quantitative MRI findings in the management of CMT. METHODS: This was a retrospective study of 160 subjects with CMT who had undergone neck MRI at the age of 48 months or younger at a tertiary medical center. Among the 160 subjects, 54 had undergone surgical release of CMT and 106 subjects had not undergone surgery. For the quantitative analysis, the rati