The Study on Automatic Annotation using Structural/Linguistic Characteristics of biomedical documents

학위논문 (박사)-- 서울대학교 대학원 : 치의과학과 의료경영정보학전공, 2015. 8. 김홍기.자동 어노테이션에 대한 연구는 급속도로 증가하는 의생명 분야의 논문 과 임상 문서들을 더욱 정확하게 검색하거나 필요한 정보만을 추출할 수 있게 하는 기반이 된다는 점에서 중요하다. 본 연구에서는, 그 중 연구 활 동에서 필수적인 논문 검색과 환자의 질병에 대한 진단, 검사, 그리고 처 방 등을 기록하는데 필수적인 임상서식의 작성에 초점을 맞추어, 이에 필 요한 어노테이션 기술을 연구하였다. 이 두 가지 활동은 의생명 분야의 대 표 문서인 논문과 임상서식을 대상으로 일상적으로 일어나는 것이며, 이 러한 활동이 효율적으로 개선되는 것은 의생명 분야에서 중요한 의미를 가진다. 먼저, 텍스트 형식의 연구 논문에 대해서는 연구 활동의 방향 설정에 중 요한 역할을 하는 초록을 대상으로, 의생명 분야에서 주로 사용하는 IMRAD(Introduction, Methods, Results, and Discussion)로의 자동 태깅을 연구하였다. 이 연구에서는, 기존 언어학 분야에서 의생명 분야의 논문을 대상으로 이룬 결과와 컴퓨터 과학 분야에서 진행돼온 결과를 기 반으로, 계산 비용이 적으면서도 높은 성능을 내는 새로운 자동 태깅 시스 템을 제안하고 개발하였다. 본 연구에서 제안한 방법을 사용하는 경우, 문 장에서 뽑아낸 17개의 특징만으로도 비구조화된 초록을 Accuracy 77.0 ~ 90.3%의 성능으로 분류할 수 있었다. 또한, 기존 연구들에서 사용한 특 징들과 함께 사용했을 때는 최대 Accuracy 91.7%의 성능을 보여주었다. 임상 문서의 경우, EMR(Electronic Medical Record)을 시스템을 사용하는 환경에서는 임상 서식을 통해 생성되는 경우가 대부분이므로, 임 상 서식을 대상으로 자동 태깅을 시도하였다. 임상 서식은 연구 초록과는 달리 이미 구조화된 형식을 가지고 있으므로, 본 연구에서는 이 구조 안에 내재된 전문가의 지식을 태깅하고자 하였다. 이를 위해 새로운 지식모델 과 이를 이용한 임상 서식 작성 지원 시스템인 STEP(Smart Clinical Document Template Editing and Production System)을 개발하였다. STEP의 시스템의 활용성을 검증하기 위해서는 임상 서식 작성 도구를 개 발하여, 지식 모델을 통해 구축된 지식베이스가 임상 서식의 작성을 개선 시킬 수 있음을 보였다. 연구 결과는 의생명 분야의 연구자들에게 대규모의 의생명 관련 논문과 임상에서 지속적으로 생산되는 임상 문서가 더욱 정확하게 검색되고 재사 용될 수 있음을 보여주고 있다. 이러한 결과는 의생명 분야 전반에서 연구 자들의 활동을 개선시킬 수 있다는 점에서 중요하다. 마지막으로, 본 연구 의 성과가 다른 연구자들에게도 활용될 수 있도록, 연구 과정에서 추출한 언어 자원과 결과를 확인할 수 있는 시스템을 웹으로 공개하였다.초 록....................................................................................................i 목 차..................................................................................................iii I. 서론................................................................................................1 1. 연구 배경 ......................................................................................1 2. 연구 목적 ......................................................................................5 3. 논문의 구성....................................................................................6 II. 구조화된 초록의 언어적 특징 추출..................................................7 1. 연구 배경 .....................................................................................7 2. 연구 목적 .....................................................................................9 3. 관련 연구 .....................................................................................9 4. 연구 방법 ................................................................................... 12 4.1. 데이터 코퍼스 ......................................................................... 13 4.2. 섹션 정규화............................................................................. 14 4.3. 섹션 맵핑 ............................................................................... 17 4.4. 언어적 특징 추출 ..................................................................... 18 5. 결과 ......................................................................................... 20 5.1. 섹션별 동사/동사구의 사용 특징 .................................................. 20 5.2. 섹션별 N-gram의 사용 특징 ...................................................... 22 5.3. 섹션별 명사(구)의 사용 특징 ....................................................... 24 5.4. 언어적 특징들의 섹션 구별력 ...................................................... 27 6. 결론 .......................................................................................... 41 III. 언어적 특징을 이용한 초록 문장 분류................................................. 44 1. 연구 배경 ................................................................................... 44 2. 연구 목적 ................................................................................... 45 3. 관련 연구 ................................................................................... 45 4. 연구 방법 ................................................................................... 48 4.1. Feature Set 구성 ................................................................... 48 4.2. 테스트 문서 집합 ...................................................................... 52 4.3. SVM을 이용한 학습 및 평가 ....................................................... 53 5. 연구 결과 ................................................................................... 54 5.1. 언어적 특징별 성능.....................................................................54 5.2. 특징 그룹 조합별 성능 ............................................................... 56 6. 논의 .......................................................................................... 65 IV. 의생명 초록 문장 자동 태깅 시스템.............................................. 67 1. 시스템 소개 ................................................................................ 67 2. 서비스 구성 ................................................................................ 67 2.1. INTRODUCTION...................................................................67 2.2 LEXICAL FEATURES ............................................................. 69 2.3 RESULTS................................................................................71 2.4 ONLINE DEMO.......................................................................73 3. Use Cases ............................................................................... 76 V. 구조적 특징을 이용한 임상 서식의 태깅 ..................................... 78 1. 연구 배경.................................................................................... 78 2. 연구 목표.................................................................................... 80 3. 임상 서식의 태깅을 위한 지식 모델 ................................................... 80 3.1. 온톨로지 ................................................................................ 80 3.2. 개념 모델 ............................................................................... 81 3.3. CDT 온톨로지......................................................................... 85 4. CDT 온톨로지를 이용한 임상서식 태깅 ............................................. 90 5. 결론 .......................................................................................... 93 VI. 임상 서식 지식베이스 기반의 서식 작성 지원 시스템 ............... 94 1. 시스템 소개 ................................................................................ 94 2. 시스템 구성 ................................................................................ 95 2.1. 지식 베이스 관리 모듈 ............................................................... 96 2.2. 핵심 모듈 ............................................................................... 96 2.3. 웹 사용자 인터페이스 .............................................................. 101 2.4. Web Services 인터페이스 ..................................................... 106 3. Use Case ...............................................................................108 4. 결론 ........................................................................................110 VII. 결론 .......................................................................................113 VIII. 연구의 제한점 및 제언 ...............................................................116 참고문헌 .......................................................................................118 부록 ............................................................................................129 Abstract .....................................................................................133Docto

Incidentally diagnosed Takayasu arteritis on thyroid ultrasonography showing prominent collateral vessels of thyroidal arteries and common carotid artery occlusion.

We report a case of middle-aged woman incidentally diagnosed with Takayasu arteritis during the ultrasonography of a thyroid gland nodule. Prominent collaterals of the thyroidal arteries and a thin common carotid artery with mural thickening and deficient intraluminal flow signals were initially depicted on the ultrasonography with color Doppler. Subsequent magnetic resonance angiography and computed tomography aortography confirmed the diagnosis with the imaging features of a bilateral long segment common carotid artery occlusion and segmental stenosis of the left subclavian artery in addition to the suggestive physical findings.ope

Ultrasound texture analysis: Association with lymph node metastasis of papillary thyroid microcarcinoma

This retrospective study aimed to evaluate whether ultrasound texture analysis is useful to predict lymph node metastasis in patients with papillary thyroid microcarcinoma (PTMC). This study was approved by the Institutional Review Board, and the need to obtain informed consent was waived. Between May and July 2013, 361 patients (mean age, 43.8 ± 11.3 years; range, 16-72 years) who underwent staging ultrasound (US) and subsequent thyroidectomy for conventional PTMC ≤ 10 mm between May and July 2013 were included. Each PTMC was manually segmented and its histogram parameters (Mean, Standard deviation, Skewness, Kurtosis, and Entropy) were extracted with Matlab software. The mean values of histogram parameters and clinical and US features were compared according to lymph node metastasis using the independent t-test and Chi-square test. Multivariate logistic regression analysis was performed to identify the independent factors associated with lymph node metastasis. Tumors with lymph node metastasis (n = 117) had significantly higher entropy compared to those without lymph node metastasis (n = 244) (mean±standard deviation, 6.268±0.407 vs. 6.171±.0.405; P = .035). No additional histogram parameters showed differences in mean values according to lymph node metastasis. Entropy was not independently associated with lymph node metastasis on multivariate logistic regression analysis (Odds ratio, 0.977 [95% confidence interval (CI), 0.482-1.980]; P = .949). Younger age (Odds ratio, 0.962 [95% CI, 0.940-0.984]; P = .001) and lymph node metastasis on US (Odds ratio, 7.325 [95% CI, 3.573-15.020]; P < .001) were independently associated with lymph node metastasis. Texture analysis was not useful in predicting lymph node metastasis in patients with PTMC.ope

Feasibility study using multifocal Doppler twinkling artifacts to detect suspicious microcalcifications in ex vivo specimens of breast cancer on US

Multifocal Doppler twinkling artifact (MDTA) imaging has shown high detection rates of microcalcifications in phantom studies. We aimed to evaluate its performance in detecting suspicious microcalcifications in comparison with mammography by using ex vivo breast cancer specimens. We prospectively included ten women with breast cancer that presented with calcifications on mammography. Both digital specimen mammography and MDTA imaging were performed for ex vivo breast cancer specimens on the day of surgery. Five breast radiologists marked cells that included suspicious microcalcifications (referred to as 'positive cell') on specimen mammographic images using a grid of 5-mm cells. Cells that were marked by at least three readers were considered as 'consensus-positive'. Matched color Doppler twinkling artifact (CDTA) signals were compared between reconstructed US-MDTA projection images and mammographic images. The median detection rate for each case was 74.7% for positive cells and 96.7% for consensus-positive cells. Of the 10 cases, 90% showed a detection rate of ≥ 80%, with 50% of cases showing a 100% detection rate for consensus-positive cells. The proposed MDTA imaging method showed high performance for detecting suspicious microcalcifications in ex vivo breast cancer specimens, and may be a feasible approach for detecting suspicious breast microcalcifications with US.ope

간의 해면상혈관종 : 역동적 자기공명영상에서의 종양내 조영증강 속도와 확산강조영상에서의 겉보기확산계수와의 관계

Dept. of Medicine/석사Purpose: To investigate the relationships between the apparent diffusion coefficients (ADCs) on diffusion-weighted imaging (DWI) and the speed of contrast-enhancement during dynamic MRI of hepatic hemangiomas.Materials and Methods: Sixty-nine hepatic hemangiomas (≥1 cm) in 47 patients underwent DWI using multiple b factors (b=50, 400, 800 s/mm2) followed by gadolinium-enhanced dynamic MRI. The lesions were classified into three groups according to the intralesional filling-in of contrast material on the portal phase images (rapid, >75%; intermediate,25%-75%; slow, <25%). Besides the ADC measured on the ADC map, ADCs were manually calculated using two different b factors (mADC50-400 with b=50 and 400; mADC400-800 with b=400 and 800s/mm2).Results: Mean ADCs (x10-3 mm2/s) were significantly higher in the rapid group than in the intermediate (p=0.046) or slow groups (p=0.002). There were significant differences between the rapid and slow groups in mADC50-400 (2.12 vs. 1.48, p=0.008) and mADC400-800 (1.68 vs. 1.22, p=0.010) and between the rapid and intermediate groups in mADC50-400(2.12 vs. 1.79, p=0.049). Comparing mADC50-400 with mADC400-800, there was a significant difference only in the rapid group (p=0.001).Conclusion: Compared with slowly-enhancing hemangiomas, higher ADCs of rapidly-enhancing hemangiomas might be related to richer intralesional vascular perfusion.restrictio

새 칫솔과 마모된 칫솔의 치태제거 효율에 관한 비교 연구

Thesis(master`s)--서울대학교 대학원 :치의학과 치주과학전공,2005.Maste

Clinicoradiologic Findings Predicting Malignancy in Papillary Lesions of Breast Diagnosed at the US-guided Core-needle Biopsy: In Regard of Complex Echogenicity

Purpose: To evaluate the clinical and sonographic findings predicting malignancy in papillary lesions of breast diagnosed at the US-guided core-needle biopsy, focusing on complex echogenicity. Materials and Methods: Retrospective review of our database was performed from January 2003 through January 2010, to identify patients with papillary lesion of breast diagnosed at the US guided core needle biopsy and performed consecutive surgical or US-guided vacuum assisted excision. We included 272 papillary lesions of breast in 251 women (mean age: 46.7± 10.0 years, mean size: 12.9 ± 11.1 mm). Of the 272 lesions, 260 (95.6%) had excised by surgery and 12 (4.4%) by US guided vacuum assisted excision. We evaluated clinical and sonographic factors predictive of malignancy. Results: 203 (74.6 %) were benign and 69 (25.4%) were malignant. Among the 203 benign lesions, 174 (85.7%) were benign papilloma, 29 (14.3%) were atypical papilloma and among the 69 malignant lesions, 44 (63.8%) were non-invasive papillary carcinoma and 25 (36.2%) were invasive papillary carcinoma. 153 (56.25%, 113 benign and 40 malignant) lesions did not show complex echogenicity and 119 (43.75%, 90 benign and 29 malignant) lesions showed complex echogenicity. Palpability (p = 0.019), lesion location (> 2 cm from nipple, p = 0.025) were factors correlated with malignancy in all papillary breast lesion. In 153 non-complex echoic papillary lesion, suspicious irregular shape (p = 0.037), larger diameter (p 2 cm from nipple, p = 0.027) was factor correlated with malignancy in papillary lesion showing complex echogenicity. Conclusion: The lesion size and irregular sonographic feature are predictive factors for malignancy in the papillary lesion without showing complex echogenicity. However, due to the lack of distinguishable sonographic feature except lesion location, we should pay attention to interpreting image feature of papillary lesion with showing complex echogenicity.ope

Significance of incidentally detected subcentimeter enhancing lesions on preoperative breast MRI: role of second-look ultrasound in lesion detection and management

OBJECTIVE. The purpose of this article is to evaluate the clinical significance of subcentimeter enhancing lesions incidentally detected on preoperative breast MRI in patients with breast cancer and the role of second-look ultrasound in lesion detection and characterization. MATERIALS AND METHODS. From January 2010 through December 2010, 180 lesions measuring less than 10 mm incidentally detected on MRI in 108 women with second-look ultrasound examinations were included (mean patient age, 47.9 years; mean [± SD] lesion size, 5.56 ± 1.64 mm). Seventy-two (40.0%) lesions were smaller than 5 mm, and 108 (60.0%) were 5 mm or larger. Of the 180 lesions, 103 (57.2%) had been biopsied or excised by localization, and 77 (42.8%) with benign ultrasound features had been followed with ultrasound for at least 2 years. Clinical and imaging features were recorded for analysis. RESULTS. Of the 180 enhancing lesions detected on MRI, 14 (7.8%) were malignant and 166 (92.2%) were benign. The malignancy rate of lesions 5 mm or larger was higher than that for lesions smaller than 5 mm (10.2% vs 4.2%), without statistical significance (p = 0.344). The washout enhancement pattern was statistically significantly associated with malignancy (p = 0.032). Although malignant ultrasound features such as nonparallel orientation were more common in malignant lesions, most malignancies had benign features, including oval shape, parallel orientation, and circumscribed margins, with BI-RADS category 4a (n = 12; 85.8%) as the final assessment. CONCLUSION. Second-look ultrasound is a feasible method for evaluating MRI-detected subcentimeter sized lesions in preoperative assessment of patients with breast cancer. A lower threshold should be applied with consideration of MRI features in deciding whether to biopsy or excise these lesions.ope

High-flow haemangiomas versus hypervascular hepatocellular carcinoma showing "pseudo-washout" on gadoxetic acid-enhanced hepatic MRI: value of diffusion-weighted imaging in the differential diagnosis of small lesions

AIM: To validate the usefulness of diffusion-weighted imaging (DWI) in the differentiation of high-flow haemangiomas showing pseudo-washout appearance on gadoxetic acid-enhanced hepatic MRI from small hypervascular hepatocellular carcinomas (HCCs). MATERIALS AND METHODS: DWI (b=50, 800 s/mm2) with apparent diffusion coefficient (ADC) maps for 50 haemangiomas (6.4±2.9 mm) showing intense enhancement on arterial dominant phase imaging and hypointensity on transitional and/or hepatobiliary phase imaging during gadoxetic acid-enhanced MRI were retrospectively analysed and compared with that of 113 hypervascular HCCs (12.8±3.7 mm). In addition to measurement of mean ADC values on DWI and contrast-to-noise ratio (CNR) on corresponding T2-weighted imaging, qualitative analysis of DWI was performed for each lesion by two independent observers using a five-point scale. RESULTS: Both of mean ADC value (1.902 versus 0.997×10-3 mm2/s) and mean CNR (119.2 versus 36.9) for haemangioma were significantly larger than for HCC (p<0.001). On receiver operating characteristic (ROC) analysis, an area under the curve (AUC) of 0.995 for ADC values was significantly larger than 0.915 for CNRs (p=0.002). When the ADC value of 1.327×10-3 mm2/s was used as the threshold for the diagnosis of haemangioma, the sensitivity and specificity were 98% and 97.3%, respectively. The mean sensitivity and specificity of qualitative analysis for the differentiation of haemangioma from HCC were 92% and 99.1%, respectively. CONCLUSION: For high-flow small haemangiomas showing pseudo-washout appearance during gadoxetic acid-enhanced hepatic MRI, high b-factor DWI including an ADC map may provide additional information to enhance the confidence to exclude small hypervascular HCCs.restrictio