• 제목/요약/키워드: intelligent medicine

검색결과 125건 처리시간 0.024초

SiMACS에서의 생체신호처리 및 데이터관리 (Signal Processing and Data Management in SiMACS)

  • 서재준;김중진;이수병;박승훈;우응제
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1994년도 춘계학술대회
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    • pp.57-59
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    • 1994
  • In this paper, we present the software part of the intelligent data processing unit (IDPU), which plays an important role in SiMACS. The software system processes ECG, EEG, EMG, blood pressure, respiration, temperature signals, and extracts some information about patient conditions. It displays the patient condition information and the signal data synchronously, and manages them together with other patient personal data in a network-based client/server environment. The software system is designed in an object-oriented paradigm, and implemented in C++ as a window-based application program.

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논문분석과 구축사례 조사를 통한 한의학 온톨로지 연구동향 분석 (A Study of Tendency Analysis to Ontology Research about Korea Medicine Using Paper and Case Study)

  • 김철;김상균;송미영
    • 한국한의학연구원논문집
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    • 제14권2호
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    • pp.121-129
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    • 2008
  • The fusion research subjects of Oriental medicine and Information-Technology are actively advanced. These researches provide Oriental medicine the objectivity and support the infra to all study area of Oriental medicine. This paper considers the inside and outside of the country technical development trend of ontology research by analyzing papers and going through case study. It executed information analysis about changes to number of research papers, present state and star higher officer of research facility from the dissertation which it sees. It is known that our country research result is slight so far in quantity and quality as result of analysis. But hereafter it contains many developmental possibilities. Also it reflects the appearance and a growth of new field like bio-informatics biology. In the area of medicine, ontology used to define the terminology for information documentation and the medical terms linked up by high correlation. Also medical information system developed briskly using ontology technology. The ontology of traditional korean medicine play an important role in base infra of traditional korean medicine EHR(Electronic health record).

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조기 위암의 내시경 영상 분석 시스템 (Analysis System of Endoscopic Image of Early Gastric Cancer)

  • 임은경;김광하;김광백
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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    • pp.255-260
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    • 2005
  • 위암은 국내 암발생 및 사망률의 상당 부분을 차지하고 있으며, 이러한 조기 위암의 발견은 치료 및 예후에 있어서 아주 중요하다. 본 논문에서는 조기 위암의 진단을 위해 위 내시경 영상에서 색상 변화를 이용해 이상 부위를 검출하여 검사자에게 조직적인 정보를 제공하는 시스템을 제안한다. 어느 정도의 진행이 이루어진 염증과 암은 쉽게 판단할 수 있지만, 조기의 염증이나 암의 경우에는 주의 깊게 보지 않는 경우에는 병변의 진단이 쉽지 않다. 본 논문에서는 위 내시경 영상을 IHB 채널로 변환시키고 조명에 의해 발생하는 잡음을 제거하며 자동으로 암 의심 영역을 검출하여 검사자에게 제공하거나 검사자에 의해 설정된 영역에 대한 조직적인 표면 정보를 제공한다. 본 논문의 연구는 추출된 이상 부위가 암을 확진할 수 없지만, 인간이 쉽게 인지하기 어려운 이상부위(암 의심 영역)를 추출하여 검사자에게 주의를 요구함으로써 일 처리를 줄이고 부과적인 정보를 제공한다. 그리고 검사추가 지정한 영역에 대해서도 조직적인 정보를 제공한다. 제안된 위 내시경 영상 분석 방법의 효율성을 확인하기 위해서 실제 내시경 영상들을 대상으로 실험한 결과, 제안된 방법이 위 내시경 영상 분석에 효율적임을 확인하였다.

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A many-objective evolutionary algorithm based on integrated strategy for skin cancer detection

  • Lan, Yang;Xie, Lijie;Cai, Xingjuan;Wang, Lifang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권1호
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    • pp.80-96
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    • 2022
  • Nowadays, artificial intelligence promotes the rapid development of skin cancer detection technology, and the federated skin cancer detection model (FSDM) and dual generative adversarial network model (DGANM) solves the fragmentation and privacy of data to a certain extent. To overcome the problem that the many-objective evolutionary algorithm (MaOEA) cannot guarantee the convergence and diversity of the population when solving the above models, a many-objective evolutionary algorithm based on integrated strategy (MaOEA-IS) is proposed. First, the idea of federated learning is introduced into population mutation, the new parents are generated through sub-populations employs different mating selection operators. Then, the distance between each solution to the ideal point (SID) and the Achievement Scalarizing Function (ASF) value of each solution are considered comprehensively for environment selection, meanwhile, the elimination mechanism is used to carry out the select offspring operation. Eventually, the FSDM and DGANM are solved through MaOEA-IS. The experimental results show that the MaOEA-IS has better convergence and diversity, and it has superior performance in solving the FSDM and DGANM. The proposed MaOEA-IS provides more reasonable solutions scheme for many scholars of skin cancer detection and promotes the progress of intelligent medicine.

조명 변화에 강인한 컬러정보 기반의 약병 분류 기법 (A Color-Based Medicine Bottle Classification Method Robust to Illumination Variations)

  • 김태훈;김기승;송영철;류강수;최병재;박길흠
    • 한국지능시스템학회논문지
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    • 제23권1호
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    • pp.57-64
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    • 2013
  • 본 논문에서는 약병의 크기와 색상정보 특징을 추출하여 약병영상 분류 기법을 제안한다. 약병영상 분류에 있어 유사한 크기와 모양을 지닌 약병이 다양하게 존재하므로, 약병의 한 가지 특징만으로는 약병을 분류하기가 어렵다. 이러한 약병의 분류 문제를 해결하기 위해 본 논문에서는 약병의 크기와 색상정보의 특징을 추출하여 약병을 분류하였다. 제안된 알고리즘의 첫 번째 단계에서는 약병영상에서 Red, Green, Blue의 이진화 문턱치(Binary threshold)를 이용하여 약병 영역의 MBR(Minimum Boundary Rectangle)을 추출하여 크기로 분류하였고, 두 번째 단계에서는 크기로 분류된 약병영상 가운데 조명의 조도 변화에 강인한 색상(Hue)정보와 RGB 각각의 채널에 대한 컬러 평균 비율 정보를 이용하여 약병을 분류하였으며, 마지막 단계에서는 SURF(Speeded Up Robust Features)알고리즘을 사용하여 데이터베이스에서 특징점을 추출한 후보군 약병영상과 입력 약병영상의 유사도가 가장 높은 약병영상을 검색하여 약병을 분류하였다. 실험을 통해 이러한 방법이 보다 효율적이고 신뢰성 있음을 입증하였다.

Robust Pelvic Coordinate System Determination for Pose Changes in Multidetector-row Computed Tomography Images

  • Kobashi, Syoji;Fujimoto, Satoshi;Nishiyama, Takayuki;Kanzaki, Noriyuki;Fujishiro, Takaaki;Shibanuma, Nao;Kuramoto, Kei;Kurosaka, Masahiro;Hata, Yutaka
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제10권1호
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    • pp.65-72
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    • 2010
  • For developing navigation system of total hip arthroplasty (THA) and evaluating hip joint kinematics, 3-D pose position of the femur and acetabulum in the pelvic coordinate system has been quantified. The pelvic coordinate system is determined by manually indicating pelvic landmarks in multidetector-row computed tomography (MDCT) images. It includes intra- and inter-observer variability, and may result in a variability of THA operation or diagnosis. To reduce the variability of pelvic coordinate system determination, this paper proposes an automated method in MDCT images. The proposed method determines pelvic coordinate system automatically by detecting pelvic landmarks on anterior pelvic plane (APP) from MDCT images. The method calibrates pelvic pose by using silhouette images to suppress the affect of pelvic pose change. As a result of comparing with manual determination, the proposed method determined the coordinate system with a mean displacement of $2.6\;{\pm}\;1.6$ mm and a mean angle error of $0.78\;{\pm}\;0.34$ deg on 5 THA subjects. For changes of pelvic pose position within 10 deg, standard deviation of displacement was 3.7 mm, and of pose was 1.28 deg. We confirmed the proposed method was robust for pelvic pose changes.

효율적인 한의 처방조제지원시스템 개발 (Development of Efficient Order Communication and Pharmacy Supporting System for Traditional Korean Medicine)

  • 김철;김상균;장현철;김안나;김익태;송미영
    • 한국한의학연구원논문집
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    • 제16권3호
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    • pp.127-133
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    • 2010
  • The purpose of this study is to develop the order communication system for Traditional Korean Medicine(TKM) which can support prescribing decisions and provide the toxicological information. The relative vulnerability of the infrastructure of TKM has made us start the study. We carried out the benchmarking for TKM charting solution firstly, and then designed the intelligent search and supporting method for prescription decisions. We developed of the medical herbs database and the web-based order communication program which can be used in medical field actually. This system supplies a various functions to oriental medical doctors such as management for prescription history, search for herb's effects, generating prescriptions, inventory management, alerting of toxicity and taboo, guideline for taking medicine, and so on. The design and implementation process has been described in this research. We expect that this system will play an important role in electronic medical record(EMR) or electronic health record(EHR) binding diagnosis and management functions.

Tongue Image Segmentation via Thresholding and Gray Projection

  • Liu, Weixia;Hu, Jinmei;Li, Zuoyong;Zhang, Zuchang;Ma, Zhongli;Zhang, Daoqiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권2호
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    • pp.945-961
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    • 2019
  • Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

데이터 기반의 세종시 교통안전망 강화 방안 연구 (Data-based Traffic Safety Strategy for Sejong City)

  • 강현정;김태홍
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.147-149
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    • 2021
  • 세종특별자치시의 교통량 폭증으로 인한 교통 문제 증가 추세는 시설 인프라의 투자로는 해결하기 어려운 수준에 이르러 데이터 기반의 지능형 교통환경 구축이 필수적이다. 교통데이터를 활용해 교통안전정책을 수립한 국내·외 사례를 알아보고 세종특별자치시 교통정보 및 데이터 활용 실태 등을 분석하여 CCTV를 활용한 주차정보 제공, 스마트 교통신호제어시스템 구축, 안전지키미 드롭존 설치방안을 제안한다. 본 연구가 향후 세종특별자치시의 교통 안전망 강화 정책 수립의 기반이 되기를 기대한다.

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Application of Artificial Intelligence for the Management of Oral Diseases

  • Lee, Yeon-Hee
    • Journal of Oral Medicine and Pain
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    • 제47권2호
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    • pp.107-108
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    • 2022
  • Artificial intelligence (AI) refers to the use of machines to mimic intelligent human behavior. It involves interactions with humans in clinical settings, and augmented intelligence is considered as a cognitive extension of AI. The importance of AI in healthcare and medicine has been emphasized in recent studies. Machine learning models, such as genetic algorithms, artificial neural networks (ANNs), and fuzzy logic, can learn and examine data to execute various functions. Among them, ANN is the most popular model for diagnosis based on image data. AI is rapidly becoming an adjunct to healthcare professionals and is expected to be human-independent in the near future. The introduction of AI to the diagnosis and treatment of oral diseases worldwide remains in the preliminary stage. AI-based or assisted diagnosis and decision-making will increase the accuracy of the diagnosis and render treatment more precise and personalized. Therefore, dental professionals must actively initiate and lead the development of AI, even if they are unfamiliar with it.