• Archives of Plastic Surgery
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• 제42권6호
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• pp.729-734
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• 2015

Background Insufficient satisfaction outcome literature exists to assist consultations for scar revision surgery; such outcomes should reflect the patient's perspective. The aim of this study was to prospectively investigate scar revision patient satisfaction outcomes, according to specified patient-selection criteria. Methods Patients (250) were randomly selected for telephone contacting regarding scar revisions undertaken between 2007-2011. Visual analogue scores were obtained for scars pre- and post-revision surgery. Surgery selection criteria were; 'presence' of sufficient time for scar maturation prior to revision, technical issues during or wound complications from the initial procedure that contributed to poor scarring, and 'absence' of site-specific or patient factors that negatively influence outcomes. Patient demographics, scar pathogenesis (elective vs. trauma), underlying issue (functional/symptomatic vs. cosmetic) and revision surgery details were also collected with the added use of a real-time, hospital database. Results Telephone contacting was achieved for 211 patients (214 scar revisions). Satisfaction outcomes were '2% worse, 16% no change, and 82% better'; a distribution maintained between body sites and despite whether surgery was functional/symptomatic vs. cosmetic. Better outcomes were reported by patients who sustained traumatic scars vs. those who sustained scars by elective procedures (91.80% vs. 77.78%, P=0.016) and by females vs. males (85.52% vs. 75.36%, P<0.05), particularly in the elective group where males (36.17%) were more likely to report no change or worse outcomes versus females (16.04%) (P<0.01). Conclusions Successful scar revision outcomes may be achieved using careful patient selection. This study provides useful information for referring general practitioners, and patient-surgeon consultations, when planning scar revision.

• 대한인간공학회지
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• 제31권4호
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• pp.601-607
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• 2012

Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.

• 대한두개안면성형외과학회지
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• 제20권1호
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• pp.17-23
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• 2019

Background: The resection of head and neck cancer can result in postoperative defect. Many patients have difficulty swallowing and masticating, and some have difficulty speaking. Various types of flaps are used for palatal reconstruction, but flap selection remains controversial. Therefore, our study will suggest which flap to choose during palatal reconstruction. Methods: Thirteen patients who underwent palatal reconstruction from 30 January, 1989 to 4 October, 2016 at our institution. Size was classified as small when the width was < $4cm^2$, medium when it was $4-6cm^2$, and large when it was ${\geq}6cm^2$. Based on speech evaluation, the subjects were divided into a normal group and an easily understood group. After surgery, we assessed whether flap selection was appropriate through the evaluation of flap success, complications, and speech evaluation. Results: Defect size ranged from $1.5{\times}2.0cm$ to $5.0{\times}6.0cm$. In four cases, the defect was in the anterior third of the palate, in eight cases it was in the middle, and there was one case of whole palatal defect. There were three small defects, two medium-sized defects, and eight large defects. Latissimus dorsi free flaps were used in six of the eight large defects in the study. Conclusion: The key to successful reconstructive surgery is appropriate selection of the flap with reference to the characteristics of the defect. Depending on the size and location of the defect, the profiles of different flaps should be matched with the recipient from the outset.

• 한국병원경영학회지
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• 제23권4호
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• pp.40-52
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• 2018

The purpose of this study is to identify medical consumers' hospital selection factors in response to the rapidly changing environment of medical industry. For that purpose this study classified consumers' hospital selection factors into three categories such that human factors including expertise, reliability, empathy; system factor including, convenience, differentiation, efficiency; and facility factor including tangibility, accessibility, and location, based on the previous studies and the results of a preliminary survey of the patients of a small private hospital. The nine factors were further divided into 23 more specific attributes. Then, an online survey was conducted to measure the perceptions of the 23 attributes by the medical consumers over the age of 20. The analysis of the survey data using Kano model and Timko model indicated that 14 of the 23 attributes were classified as attractive factors, eight attributes were or classified as, one-dimensional factors, and one attribute, doctors' educational background, was classified as indifference factor. Of the 14 attractive factors, "unique and differentiated services related to medical treatment" and "distance from home to hospital" had the highest customer satisfaction coefficients. Of the eight one-dimensional factors, "kind treatment," "providing adequate explanations," "accuracy of diagnosis," and "cleanness of facilities" had the highest customer satisfaction coefficients as well as the highest dissatisfaction coefficients. The findings indicate that these six attributes are the most basic and most impactful attributes that hospitals must manage strategically to improve their service quality and attract more medical consumers to their hospitals.

• 한국임상약학회지
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• 제34권2호
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• pp.134-139
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• 2024

Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

• 정보관리학회지
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• 제29권2호
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• pp.205-224
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• 2012

자동 분류에서 문헌을 표현하는 일반적인 방식인 BOW는 용어를 독립적으로 처리하기 때문에 주변 문맥을 반영하지 못한다는 한계가 있다. 이에 본 연구는 각 용어마다 주제범주별 문맥적 특징을 파악해 프로파일로 정의하고, 이 프로파일과 실제 문헌에서의 문맥을 비교하는 과정을 통해 동일한 형태의 용어라도 그 의미나 주제적 배경에 따라 구분하고자 하였다. 이를 통해 주제가 서로 다름에도 불구하고 특정 용어의 출현만으로 잘못된 분류 판정을 하는 문제를 극복하고자 하였다. 본 연구에서는 이러한 문맥적 요소를 용어 가중치, 분류기 결합, 자질선정의 3가지 항목에 적용해 보고 그 분류 성능을 측정했다. 그 결과, 세 경우 모두 베이스라인보다 분류 성능이 향상되었고 가장 큰 성능 향상을 보인 것은 분류기 결합이었다. 또한 제안한 방법은 학습문헌 수가 많고 적음에 따라 발생하는 성능의 편향을 완화하는데도 효과적인 것으로 나타났다.

• 한국컴퓨터정보학회논문지
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• 제10권1호
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• pp.67-72
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• 2005

대부분의 이진화 알고리즘은 임계치를 결정하기 위하여 히스토그램을 사용하여 밝기 분포를 분석한다. 배경과 물체의 명도차이가 큰 경우에는 양봉 형태의 히스토그램이 나타나며 최적의 임계치를 찾기 위해 히스토그램 골짜기를 선택하는 것만으로도 양호한 임계치 결과를 얻을 수 있다. 반면에 배경과 물체의 밝기 차이가 크지 않거나 밝기 분포가 양봉 특성을 보이지 않을 때는 히스토그램 분석만으로 적절한 임계치를 얻기 어렵다 본 논문에서는 RGB 컬러 모형의 각 색상에 대하여 퍼지 소속 함수를 적용하고, 그 결과를 이용해 배경에 비해 가독성이 높은 특징들을 배경과 분리하는 방법을 제안한다. 제안된 이진화 방법은 RGB의 각 색상에 퍼지 소속 함수를 적용하여 얻은 값들을 이용해 이진화한다. 기존의 임계치를 이용한 이진화 방법에 비해 잡음 영역을 상당히 제거 할 수 있으며, 운송 컨테이너 영상에 적용한 결과, 기존의 방법에 비해 효율적인 것을 확인하였다.

• 대한치위생과학회지
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• 제5권2호
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• pp.25-33
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• 2022

Background: This study was aimed at investigating factors influencing the selection of dental institutions for implant surgery among young adults (age: 20-64 years) and identifying differences in these factors according to general characteristics. Methods: We conducted an internet survey for approximately 2 months, from April to July 2022, and analyzed data from a total of 128 people. Dental institution selection factors included three items of convenience of transportation, five items of physical environment, three items of image of institution, five items of image of dental staff, five items of dental service, and four items of basic dental elements. The importance score for each item was investigated on a five-point scale. Results: The importance score for each dental institution selection factor was the highest for dental service (4.42 points), followed by basic dental element (4.00 points), physical environment (3.89 points), image of institution (3.81 points), convenience of transportation (3.76 points), and image of dental staff (2.78 points). The importance score for each item was the highest for dentists' technique, followed by cleanliness, reliability, and dentists' attitude. Women had higher average scores for all factors compared to men, with statistical significance in scores for convenience of transportation, physical environment, image of institution, dental service, and basic dental elements (p< 0.05). Conclusion: To attract patients seeking implants to a dental institution, attention should be paid to the patients' institution selection factors. In addition, the environment of a dental institution should be created in such a way that it favors patients' selection factors.

• 한국조리학회지
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• 제16권3호
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• pp.114-129
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• 2010

본 연구의 목적은 첫째 무드를 효과적으로 조성하기 위한 장르와 템포를 제시할 수 있으며, 둘째, 호텔 내 레스토랑과 테마 레스토랑 유형별 적합한 배경음악의 장르와 템포를 제시하여 호텔과 레스토랑 경영자들이 활용할 수 있도록 하는 것이다. 본 연구의 결과로부터 음악의 장르와 템포에 의해 고객의 무드에 영향을 미치고 만족 및 재방문, 추천의사에 유의한 영향을 준다는 사실을 확인할 수 있었다. 예를 들어 업장 분위기에 변화를 주고 싶다면 시간적, 금전적인 감수가 필요한 리모델링을 보다는 배경음악의 변화가 훨씬 용이할 것이며, 업장의 컨셉이 확정되었다면 그 컨셉을 더 표출해 줄 수 있는 것이 음악이며, 고객의 특정 감정에 호소하기 위해서는 본 연구에서 제시하고 있는 장르와 템포대로 곡을 선정할 수 있을 것이다. 예를 들어 편안하고 긍정적인 감정을 유발하기 위해서는 느린 템포를, 친숙하고 행복한 감정을 위해서는 중간 템포를, 기쁨과 호감을 위해서는 빠른 템포가 적합하다는 것이다. 편안함을 유발시킨 느린 템포는 고객의 업장 내에서의 체류시간 길게 할 것이며, 반대로 빠른 템포는 체류시간을 감소시킬 것이다. 이를 활용하여 좌석회전율을 높이기 위해선 빠른 템포의 음악 선정할 수 있을 것이다. 고객의 감정을 음악으로 조율하여 고객 만족과 재무성과의 목표를 동시에 달성할 수 있을 것이라는 사실을 제안한다.

• 한국음향학회지
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• 제22권5호
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• pp.360-366
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• 2003

다층신경망 (multilayer perceptron)이 다른 패턴인식 방법에 비해 여러 가지 이점을 제공하지만 다층신경망에 기반한 화자증명 시스템은 낮은 증명오류를 달성하기 위한 대규모 배경화자로 인한 느린 등록속도의 문제를 안는다. 이 문제를 해결하기 위해 QnDCS(quantitative discriminative cohort speakers) 방법에서 화자군집 방법을 다층신경망 기반화자증명 시스템에 도입하여 화자등록에 필요한 배경화자의 수를 줄이려는 시도가 있었다. QnDCS 방법이 목적을 어느 정도 달성하긴 했지만 등록속도의 향상률이 만족할만한 수준이지 못했다. 본 논문에서는 보다 높은 등록속도 향상률을 달성하기 위한 방법으로서, 선택되는 배경화자의 수를 더욱 낮추는 정질에 기반한 기준을 도입한 QlDCS (qualitative discriminative cohort speakers) 방법을 제안한다. 두 방법에 대한 성능평가를 위해 다층신경망과 지속음에 기반한 화자증명 시스템과 음성 데이터베이스를 사용한 실험을 실시한다 그 결과 제안한 방법이 QlDCS에 비해 온라인 방식의 EBP (error backpropagation)에 대한 학습속도 향상률 면에서 2배 이상 더 짧은 시간 내에 화자를 등록하는 것으로 나타나 보다 높은 효율을 지녔음을 증명한다.