• Annual Conference of KIPS
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• 2019.05a
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• pp.383-386
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• 2019

4 차산업혁명의 발달은 전 세계가 건강한 삶에 관련된 스마트시티 및 맞춤형 치료에 큰 관심을 갖게 하였고, 특히 기계학습 기술은 암을 극복하기 위한 유전체 기반의 정밀 의학 연구에 널리 활용되고 있어 암환자의 예후 예측 및 예후에 따른 맞춤형 치료 전략 수립 등을 가능케하였다. 하지만 암 예후 예측 연구에 주로 사용되는 유전자 발현량 데이터는 약 17,000 개의 유전자를 갖는 반면에 샘플의 수가 200 여개 밖에 없는 문제를 안고 있어, 예후 예측을 위한 신경망 모델의 일반화를 어렵게 한다. 이러한 문제를 해결하기 위해 본 연구에서는 고차원의 유전자 발현량 데이터를 신경망 모델이 효과적으로 학습할 수 있도록 2D 이미지로 표현하는 기법을 제안한다. 길이 17,000 인 1 차원 유전자 벡터를 64×64 크기의 2 차원 이미지로 사상하여 입력크기를 압축하였다. 2 차원 평면 상의 유전자 좌표를 구하기 위해 유전자 네트워크 데이터와 Node2Vec 이 활용되었고, 이미지 기반의 암 예후 예측을 수행하기 위해 합성곱 신경망 모델을 사용하였다. 제안하는 기법을 정확하게 평가하기 위해 이중 교차 검증 및 무작위 탐색 기법으로 모델 선택 및 평가 작업을 수행하였고, 그 결과로 베이스라인 모델인 고차원의 유전자 벡터를 입력 받는 다층 퍼셉트론 모델보다 더 높은 예측 정확도를 보여주는 것을 확인하였다.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.387-393
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• 2018

Objectives: This paper describes an experience of implementing seamless service trials online and offline by adopting Internet of Things (IoT) technology based on near-field communication (NFC) tags and Bluetooth low-energy (BLE) beacons. The services were provided for both patients and health professionals. Methods: The pilot services were implemented to enhance healthcare service quality, improve patient safety, and provide an effective business process to health professionals in a tertiary hospital in Seoul, Korea. The services to enhance healthcare service quality include healing tours, cancer information/education, psychological assessments, indoor navigation, and exercise volume checking. The services to improve patient safety are monitoring of high-risk inpatients and delivery of real-time health information in emergency situations. In addition, the services to provide an effective business process to health professionals include surveys and web services for patient management. Results: Considering the sustainability of the pilot services, we decided to pause navigation and patient monitoring services until the interference problem could be completely resolved because beacon signal interference significantly influences the quality of services. On the other hand, we had to continue to provide new wearable beacons to high-risk patients because of hygiene issues, so the cost increased over time and was much higher than expected. Conclusions: To make the smart connected hospital services sustainable, technical feasibility (e.g., beacon signal interference), economic feasibility (e.g., continuous provision of new necklace beacons), and organizational commitment and support (e.g., renewal of new alternative medical devices and infrastructure) are required.

• Journal of Multimedia Information System
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• v.9 no.3
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• pp.233-244
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• 2022

A MATLAB program was developed to calculate the half-wavelength of a sine-curve baseband signal with white noise by using an autocorrelation function, a SG filter, and zero-crossing detection. The frequency of the input signal can be estimated from 1) the first zero-crossing (corresponding to ¼λ) and 2) the R value (the Y axis of the correlogram) at the center of the segment. Thereby, the frequency information of the preceding segment can be obtained. If the segment size were optimized, and a portion with a large zero-crossing dynamic range were obtained, the frequency discrimination ability would improve. Furthermore, if the values of the correlogram for each frequency prepared on the CPU side were prepared in a table, the volume of calculations can be reduced by 98%. As background, period detection by autocorrelation coefficients requires an integer multiple of 1/2λ (when using a sine wave as the object of the autocorrelation function), otherwise the correlogram drawn by R value will not exhibit orthogonality. Therefore, it has not been used in bio-telemetry where the frequencies move around.

• Journal of Hospice and Palliative Care
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• v.26 no.1
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• pp.1-6
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• 2023

This paper aimed to summarize the current situation of prognostication for patients with an expected survival of weeks or months, and to clarify future research priorities. Prognostic information is essential for patients, their families, and medical professionals to make end-of-life decisions. The clinician's prediction of survival is often used, but this may be inaccurate and optimistic. Many prognostic tools, such as the Palliative Performance Scale, Palliative Prognostic Index, Palliative Prognostic Score, and Prognosis in Palliative Care Study, have been developed and validated to reduce the inaccuracy of the clinician's prediction of survival. To date, there is no consensus on the most appropriate method of comparing tools that use different formats to predict survival. Therefore, the feasibility of using prognostic scales in clinical practice and the information wanted by the end users can determine the appropriate prognostic tool to use. We propose four major themes for further prognostication research: (1) functional prognosis, (2) outcomes of prognostic communication, (3) artificial intelligence, and (4) education for clinicians.

• Annual Conference of KIPS
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• 2020.11a
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• pp.784-787
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• 2020

폐암 환자의 생존율을 예측할 때 미국암연합회(AJCC)의 TNM병기 분류체계에 의해 진단되는 최종병기를 많이 사용한다. 최종병기는 폐암환자의 임상데이터 중 하나로 종양의 위치, 크기, 전이정도를 고려하여 환자의 폐암 상태를 판별하는 정보이다. 최종병기는 개략적인 환자의 상황을 설명하는 데 효과적이지만, 보다 구체적인 생존분석을 위해서는 임상데이터 뿐만 아니라 PET/CT와 같은 영상 데이터를 함께 분석해야 한다. 이 논문에서는 데이터 과학적 접근을 통해 폐암환자의 임상데이터, CT영상과 PET영상 등 다양한 종류의 데이터를 함께 활용하는 생존분석기법을 검토한다. 실험을 통해 다중 모드 데이터를 활용하는 생존분석을 위해 비선형모델 개발과 Feature임베딩 기법 고도화가 필요함을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.307-310
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• 2021

In the recent years, studies using Computer-Aided Diagnostics(CAD) have been actively conducted, such as signal and image processing technology using breast ultrasound images, automatic image optimization technology, and automatic detection and classification of breast masses. As computer diagnostic technology is developed, it is expected that early detection of cancer will proceed accurately and quickly, reducing health insurance and test ice for patients, and eliminating anxiety about biopsy. In this paper, a quantitative analysis of tumors was conducted in ultrasound images using a gray level co-occurrence matrix(GLCM) to experiment with the possibility of use for computer assistance diagnosis.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.313-315
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• 2023

본 논문에서는 ¹⁸F-FDG PET과 CT에서 추출한 영상인자를 이용하여 비소세포폐암의 전이를 예측하는 머신러닝 모델을 생성하였다. ¹⁸F-FDG는 종양의 포도당 대사 시 사용되며 이를 추적하여 환자의 암 세포를 진단하는데 사용되는 의료영상 기법 중 하나이다. PET과 CT 영상에서 추출한 이미지 특징은 종양의 생물학적 특성을 반영하며 해당 ROI로부터 계산되어 정량화된 값이다. 본 연구에서는 환자의 의료영상으로부터 image texture 프절 전이 예측에 있어 유의한 인자인지를 확인하기 위하여 AUC를 계산하고 단변량 분석을 진행하였다. PET과 CT에서 각각 4개(GLRLM_GLNU, SHAPE_Compacity only for 3D ROI, SHAPE_Volume_vx, SHAPE_Volume_mL)와 2개(NGLDM_Busyness, TLG_ml)의 image texture feature를 모델의 생성에 사용하였다. 생성된 각 모델의 성능을 평가하기 위해 accuracy와 AUC를 계산하였으며 그 결과 random forest(RF) 모델의 예측 정확도가 가장 높았다. 추출된 PET과 CT image texture feature를 함께 사용하여 모델을 훈련하였을 때가 각각 따로 사용하였을 때 보다 예측 성능이 개선됨을 확인하였다. 추출된 영상인자가 림프절 전이를 나타내는 바이오마커로서의 가능성을 확인할 수 있었으며 이러한 연구 결과를 바탕으로 개인별 의료 영상을 기반으로 한 비소세포폐암의 치료 전략을 수립할 수 있을 것이라 기대된다.

• The Journal of Korean Society for Radiation Therapy
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• v.23 no.1
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• pp.21-29
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• 2011

Purpose: The purpose of this master's thesis is to utilize basic data in order to improve the quality of life of cancer patients who received radiation therapy after analysing related factors that influence patient's quality of life and obtaining information about physical, mental problems of patients. Materials and Methods: By using a structured questionnaire about various characteristics and forms of support, I carried out a survey targeting 107 patients that experienced radiation therapy at a university hospital in the Daejeon metropolitan area from July 15 to August 15, 2010 and analysed the factors influencing quality of life. Results: In case of pain due to disease, 65.15 and painless 81.87 showed a high grade quality of life. As body weight decreases, the quality of life become lower. When the grade of quality of life according to economic characteristics was compared, all items except treatment period showed a difference (P=0.000). When the score of social support, family support, medical support and self-esteem was low, the mark of quality of life showed respectively 61.71, 68.77, 71.31, and 69.39 on the basis of 128 points. When the score of support form was high, the mark of quality of life showed 90.47, 83.29, 90.40, and 90.36 (P<0.05). When analyzing the correlation between social support, family support, medical support and self-esteem and the degree of quality of life, social support was 0.768, family support 0.596, medical support 0.434, self-esteem 0.516. They indicated the correlation of meaningful quantity statistically (P<0.01). The factors that improved the quality of life were married state, having a job and painless status. As monthly income increases, the quality of life was also much improved (P<0.05). Among the factors related to quality of life, social support and medical support and higher self-esteem scores of the quality of life score increased 0.979 point, 0.508 points and 1.667 point, respectively. Conclusion: In conclusion, the quality of life of cancer patients that received radiation treatment is related to social support, medical support and self esteem. Self-esteem is an important factor that influenced quality of life, so if government offers works that doesn't affect patient's health, they are a useful method that maximize self-esteem and lessen their financial burden at the same time. Along with these policies, the developments of the attention of medical and the program for cancer patient's family are needed for the purpose of improving quality of life of cancer patients. Lastly, medical team, patients and family have to cooperate in harmony to overcome difficulties of cancer patients.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.9-17
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• 2004

Purpose : Although Improve of CT, MRI Radio-diagnosis and Radiation Therapy Planing, but we still use ICRU38 Planning system(2D film-based) broadly. 3-Dimensional ICR plan(CT image based) is not only offer tumor and normal tissue dose but also support DVH information. On this study, we plan irradiation-goal dose on CTV(CTV plan) and irradiation-goal dose on ICRU 38 point(ICRU38 plan) by use CT image. And compare with tumor-dose, rectal-dose, bladder-dose on both planning, and analysis DVH Method and Material : Sample 11 patients who treated by Ir-192 HDR. After 40Gy external radiation therapy, ICR plan established. All the patients carry out CT-image scanned by CT-simulator. And we use PLATO(Nucletron) v.14.2 planing system. We draw CTV, rectum, bladder on the CT image. And establish plan irradiation-$100\%$ dose on CTV(CTV plan) and irradiation-$100\%$ dose on A-point(ICRU38 plan) Result : CTV volume($average{\pm}SD$) is $21.8{\pm}26.6cm^3$, rectum volume($average{\pm}SD$) is $60.9{\pm}25.0cm^3$, bladder volume($average{\pm}SD$) is $116.1{\pm}40.1cm^3$ sampled 11 patients. The volume including $100\%$ dose is $126.7{\pm}18.9cm^3$ on ICRU plan and $98.2{\pm}74.5cm^3$ on CTV plan. On ICRU planning, the other one's $22.0cm^3$ CTV volume who residual tumor size excess 4cm is not including $100\%$ isodose. 8 patient's $12.9{\pm}5.9cm^3$ tumor volume who residual tumor size belows 4cm irradiated $100\%$ dose. Bladder dose(recommended by ICRU 38) is $90.1{\pm}21.3\%$ on ICRU plan, $68.7{\pm}26.6\%$ on CTV plan, and rectal dose is $86.4{\pm}18.3\%,\;76.9{\pm}15.6\%$. Bladder and Rectum maximum dose is $137.2{\pm}50.1\%,\;101.1{\pm}41.8\%$ on ICRU plan, $107.6{\pm}47.9\%,\;86.9{\pm}30.8\%$ on CTV plan. Therefore CTV plan more less normal issue-irradiated dose than ICRU plan. But one patient case who residual tumor size excess 4cm, Normal tissue dose more higher than critical dose remarkably on CTV plan. $80\%$over-Irradiated rectal dose(V80rec) is $1.8{\pm}2.4cm^3$ on ICRU plan, $0.7{\pm}1.0cm^3$ on CTV plan. $80\%$over-Irradiated bladder dose(V80bla) is $12.2{\pm}8.9cm^3$ on ICRU plan, $3.5{\pm}4.1cm^3$ on CTV plan. Likewise, CTV plan more less irradiated normal tissue than ICRU38 plan. Conclusion : Although, prove effect and stability about previous ICRU plan, if we use CTV plan by CT image, we will reduce normal tissue dose and irradiated goal-dose at residual tumor on small residual tumor case. But bigger residual tumor case, we need more research about effective 3D-planning.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.83-126
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• 2005

Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.