배정호 교수

기존 영화 산업에서 구전의 크기는 매출에 영향을 주지만 방향성은 영향을 주지 못하는 것으로 연구되었다(Liu 2006). 하지만, 이러한 분석 방법을 국내 영화 데이터에 동일하게 적용시켜 본 결과, 구전의 방향성도 영화의 매출에 영향을 주는 것으로 밝혀졌다. 이는 아시아 지역의 소비자들에게서 나타나는 독립적 자아관점과 북미 지역의 소비자들에게서 나타나는 상호의존적 자아관점의 차이로 인해 나타난 결과로 보인다. 즉, 국내 소비자의 경우는 영화를 선택/관람함에 있어 타인의 평가가 영향력을 주기 때문에 구전의 방향성도 유의한 양(+)의 값을 가진다. 기존의 연구에서는 구전의 크기가 일방적으로 매출에 영향을 미친다는 가정을 통해 영화 산업의 구전효과를 분석했으나, 이는 발생된 매출이 구전의 크기에 미치는 영향을 간과한 것이다. 따라서 매출이 구전에 미치는 효과까지 고려하여 연립방정식(Simultaneous Equation)을 통해 구전의 크기와 매출 간 상호 관계를 추정한 결과, 구전의 방

BACKGROUND: Although colonoscopy is useful for differentiating between Crohn's disease (CD) and intestinal tuberculosis (ITB), the technique has limitations. We developed a practical prediction model for differentiating between CD and ITB using laboratory and radiologic parameters and colonoscopic characteristics. METHODS: We prospectively enrolled 80 patients newly diagnosed with CD (n = 40) and ITB (n = 40). We developed a new prediction score by integrating colonoscopic, laboratory, and radio

최근 기업의 사회적 책임은 글로벌 기업의 핵심 경영 주제로 부각되고 있다. 일부 국내 기업들도 기업의 사회적 책임을 실천하기 위해 금전적 기부, 사회봉사활동, 장애인 고용 등 사회공헌활동에 참여하기 시작했다. 그러나 국내 기업들은 사회적 공헌활동의 필요성에 대해 원론적으로 공감하면서 사회공헌활동에 대한 투자에는 아직 소극적인 것 같다. 그 이유는 사회공헌활동의 재무적 성과를 정확히 측정한 경험이 없고 대부분 기업은 사회공헌활동을 투자로 인식하기 보다는 비용으로 인식하는 경향이 지배적이기 때문이다. 본 연구의 목적은 기업의 사회공헌활동 및 관련 투자 효과를 정량적으로 측정하는 데 있다. 사건연구 방법론을 통해 2001년 1월 1일부터 2006년 11월 31일까지 사회공헌활동이 언론에 공개된 100개 국내 기업에 대해 분석한 결과에 따르면, 사회공헌활동 및 관련 투자는 사건당일과 사건 직전일의 비정상 수익률 합의 평균이 1.04%로 나타났다. 이는 시가총액 기준으로 약 1000억 원에

Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. To be an effective system, it is important to detect additional polyps that may be easily missed by endoscopists. Sessile serrated lesions (SSLs) are a precursor to colorectal cancer with a relatively higher miss rate, owing to their flat and subtle morphology. Colonoscopy CADe systems could help endoscopists; however, the current systems exhibit a very low performance for detecting SSLs. We

The UML metamodel has been increased in its size and complexity due to many needs for supporting various platforms and domains. The large size of the metamodel can prevent tool developers from understanding the UML metamodel and thus from developing UML-based tools. In this paper, we propose an approach to managing the complexity of the UML metamodel by modularizing the metamodel into a set of small metamodels for each UML diagram type. To that goal, we propose a slicing algorithm for extracting

BACKGROUND: Manual data extraction of colonoscopy quality indicators is time and labor intensive. Natural language processing (NLP), a computer-based linguistics technique, can automate the extraction of important clinical information, such as adverse events, from unstructured free-text reports. NLP information extraction can facilitate the optimization of clinical work by helping to improve quality control and patient management. OBJECTIVE: We developed an NLP pipeline to analyze free-text colo

This study evaluated the impact of differing false positive (FP) rates in two computer-aided detection (CADe) systems on the clinical effectiveness of artificial intelligence (AI)-assisted colonoscopy. The primary outcomes were adenoma detection rate (ADR) and adenomas per colonoscopy (APC). The ADR in the control, system A (3.2% FP rate), and system B (0.6% FP rate) groups were 44.3%, 43.4%, and 50.4%, respectively, with system B showing a significantly higher ADR than the control group. The AP

Abstract Diverticulosis results from complex interactions related to aging, environmental factors and genetic predisposition. Despite epidemiologic evidence of genetic risk factors, there has been no attempt to identify genes that confer susceptibility to colonic diverticulosis. We performed the first genome-wide association study (GWAS) on susceptibility to diverticulosis in a Korean population. A GWAS was carried out in 7,948 healthy individuals: 893 patients and 1,075 controls comprised the t

OBJECTIVES: Many interventions have been attempted to improve adenoma detection rate (ADR) and sessile serrated lesion detection rate (SDR), and one of these interventions is educational training to recognize polyp characteristics. This study aimed to investigate the change in polyp detection rates of endoscopists before and after comprehensive training through the Gangnam-Real Time Optical Diagnosis (Gangnam-READI) program. METHODS: Fifteen gastroenterologists participated in a 1-year comprehen

Background and Aims: The utility of clinical information from esophagogastroduodenoscopy (EGD) reports has been limited because of its unstructured narrative format. We developed a natural language processing (NLP) pipeline that automatically extracts information about gastric diseases from unstructured EGD reports and demonstrated its applicability in clinical research. Methods: An NLP pipeline was developed using 2000 EGD and associated pathology reports that were retrieved from a single healt

Recognizing anatomical sections during colonoscopy is crucial for diagnosing colonic diseases and generating accurate reports. While recent studies have endeavored to identify anatomical regions of the colon using deep learning, the deformable anatomical characteristics of the colon pose challenges for establishing a reliable localization system. This study presents a system utilizing 100 colonoscopy videos, combining density clustering and deep learning. Cascaded CNN models are employed to esti

Adequate bowel preparation is an important factor in high-quality colonoscopy. It is generally accepted that a Boston Bowel Preparation Scale (BBPS) score ≥ 6 is adequate, but some reports suggest ≥ 7. Subjects who underwent colonoscopy at least twice within 3 years from August 2015 to December 2019 were included. Polyp detection rates (PDRs), adenoma detection rates (ADRs), and number of polyps including adenomas were compared stratified by baseline colonoscopy (C1) BBPS score. Among 2352 subje