• Title/Summary/Keyword: infection algorithm

검색결과 61건 처리시간 0.026초

한국형 노인요양시설 근거중심 감염관리 가이드라인 개발 (Development of Evidence-based Guidelines for Nursing Home's Infection Control in Korea)

  • 박연환;이성현;이유미;이지영;이민혜
    • 근관절건강학회지
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    • 제25권2호
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    • pp.135-147
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    • 2018
  • Purpose: The purpose of this study was to develop evidence-based guidelines for infection control in nursing homes in Korea (ENIK). Methods: Three steps were planned for the development which were developing a draft and testing the content validity. First, the draft was based on evidence and developed through focus group interviews with nurses in nursing homes, a comprehensive review of international guidelines and literature, and systematic reviews of interventions for infection control and outbreaks in long-term care facilities. Clinical applicability was established through reviews of nursing records and job assignments in one nursing home. The final step consisted of experts evaluating the content validity. The ENIK was revised to fit Korean nursing homes. Results: The ENIK consisted of recommendations in 9 compositions and a one-page practical algorithm. The principles of infection control were presented by statements and specific strategies were recommended in resident care programs. The infection control practical algorithm was organized into 3 steps: screening at admission, prevention, and control at the early stage. The practice to control infection was composed of a 5-step process. Conclusion: The ENIK will contribute to improving the competency of infection control practice because it provides standardized practice and is tailored to Korean nursing homes.

잎사귀 영상처리기반 질병 감지 알고리즘 (Disease Detection Algorithm Based on Image Processing of Crops Leaf)

  • 박정현;이성근;고진광
    • 한국빅데이터학회지
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    • 제1권1호
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    • pp.19-22
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    • 2016
  • 최근 IT 기술을 활용하여 농작물의 병충해 조기 진단에 관한 연구가 활발히 진행되고 있다. 본 논문은 카메라 센서를 통해 받아온 작물의 잎사귀 이미지를 분석하여 병충해를 조기에 감지할 수 있는 이미지 프로세싱 기법에 대해 논한다. 본 논문은 개선된 K 평균 클러스터링 방법을 활용하여 잎사귀 질병 감염 여부를 진단하는 알고리즘을 제안한다. 잎사귀 감염 분류 실험을 통해, 제안한 알고리즘이 정성적인 평가에서 더 좋은 성능을 나타낸 것으로 분석되었다.

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Sternoclavicular Joint Infection: Classification of Resection Defects and Reconstructive Algorithm

  • Joethy, Janna;Lim, Chong Hee;Koong, Heng Nung;Tan, Bien-Keem
    • Archives of Plastic Surgery
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    • 제39권6호
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    • pp.643-648
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    • 2012
  • Background Aggressive treatment of sternoclavicular joint (SCJ) infection involves systemic antibiotics, surgical drainage and resection if indicated. The purpose of this paper is to describe a classification of post resectional SCJ defects and highlight our reconstructive algorithm. Defects were classified into A, where closure was possible often with the aid of topical negative pressure dressing; B, where parts of the manubrium, calvicular head, and first rib were excised; and C, where both clavicular, first ribs and most of the manubrium were resected. Methods Twelve patients (age range, 42 to 72 years) over the last 8 years underwent reconstruction after SCJ infection. There was 1 case of a type A defect, 10 type B defects, and 1 type C defect. Reconstruction was performed using the pectoralis major flap in 6 cases (50%), the latissimus dorsi flap in 4 cases (33%), secondary closure in 1 case and; the latissimus and the rectus flap in 1 case. Results All wounds healed uneventfully with no flap failure. Nine patients had good shoulder motion. Three patients with extensive clavicular resection had restricted shoulder abduction and were unable to abduct their arm past $90^{\circ}$. Internal and external rotation were not affected. Conclusions We highlight our reconstructive algorithm which is summarised as follows: for an isolated type B SCJ defect we recommend the ipsilateral pectoralis major muscle for closure. For a type C bilateral defect, we suggest the latissimum dorsi flap. In cases of extensive infection where the thoracoacromial and internal mammary vessels are thrombosed, the pectoralis major and rectus abdominus cannot be used; and the latissimus dorsi flap is chosen.

Regression analysis of doubly censored failure time data with frailty time data with frailty

  • Kim Yang-Jin
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2004년도 학술발표논문집
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    • pp.243-248
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    • 2004
  • The timings of two successive events of interest may not be measurable, instead it may be right censored or interval censored; this data structure is called doubly censored data. In the study of HIV, two such events are the infection with HIV and the onset of AIDS. These data have been analyzed by authors under the assumption that infection time and induction time are independent. This paper investigates the regression problem when two events arc modeled to allow the presence of a possible relation between two events as well as a subject-specific effect. We derive the estimation procedure based on Goetghebeur and Ryan's (2000) piecewise exponential model and Gauss-Hermite integration is applied in the EM algorithm. Simulation studies are performed to investigate the small-sample properties and the method is applied to a set of doubly censored data from an AIDS cohort study.

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Novel Diagnostic Algorithm Using tuf Gene Amplification and Restriction Fragment Length Polymorphism is Promising Tool for Identification of Nontuberculous Mycobacteria

  • Shin, Ji-Hyun;Cho, Eun-Jin;Lee, Jung-Yeon;Yu, Jae-Yon;Kang, Yeon-Ho
    • Journal of Microbiology and Biotechnology
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    • 제19권3호
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    • pp.323-330
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    • 2009
  • Nontuberculous mycobacteria (NTM) are a major cause of opportunistic infections in immunocompromised patients, making the reliable and rapid identification of NTM to the species level very important for the treatment of such patients. Therefore, this study evaluated the usefulness of the novel target genes tuf and tmRNA for the identification of NTM to the species level, using a PCRrestriction fragment length polymorphism analysis (PRA). A total of 44 reference strains and 17 clinical isolates of the genus Mycobacterium were used. The 741 bp or 744 bp tuf genes were amplified, restricted with two restriction enzymes (HaeIII/MboI), and sequenced. The tuf gene-PRA patterns were compared with those for the tmRNA (AvaII), hsp65 (HaeIII/HphI), rpoB (MspI/HaeIII), and 16S rRNA (HaeIII) genes. For the reference strains, the tuf gene-PRA yielded 43 HaeIII patterns, of which 35 (81.4%) showed unique patterns on the species level, whereas the tmRNA, hsp65, rpoB, and 16S rRNA-PRAs only showed 10 (23.3%), 32 (74.4%), 19 (44.2%), and 3 (7%) unique patterns after single digestion, respectively. The tuf gene-PRA produced a clear distinction between closely related NTM species, such as M. abscessus (557-84-58) and M. chelonae (477-84-80-58), and M. kansasii (141-136-80-63-58-54-51) and M. gastri (141-136-117-80-58-51). No difference was observed between the tuf-PRA patterns for the reference strains and clinical isolates. Thus, a diagnostic algorithm using a tuf gene-targeting PRA is a promising tool with more advantages than the previously used hsp65, rpoB, and 16S rRNA genes for the identification of NTM to the species level.

바이러스 감염 판별용 혈액 검사기 개발 (The development of Inspection Machine for a blood virus infection)

  • 전재민;서규태;이보희;이인구;민승기;김학준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.465-467
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    • 2004
  • This paper deals with the design and analysis of automatic virus infection machine, which can be used in blood testing at veterinary hospital. It consists of the mechanical positioning parts and electrical control parts. Two of driving motor and ball screws are used to move the liquid container into the test position and mix the blood on litmus paper. In addition, a thermal controller is installed to keep the container temperature on constant level. The user interface using with a LCD and some keys are supplied with a 8-bit single chip controller. All of the designs issue related with the mechanism and controllers are discussed in detail. Finally the proposed machine is tested in real experiment with the formal processing to judge the virus infection, and also the usefulness of designed algorithm is verified through the experiments.

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입원 환자의 욕창예방과 중재를 위한 알고리즘 개발 (Development of an Algorithm for the Prevention and Management of Pressure Ulcers)

  • 김진미;박정숙
    • 성인간호학회지
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    • 제22권4호
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    • pp.353-364
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    • 2010
  • Purpose: The purpose of this study was to develop an algorithm for preventing and managing of pressure ulcer and to verify the its appropriateness. Methods: The first step was development of a pre-algorithm through a literature review and expert opinion. The second step was to establish content validity by submitting the algorithm questionnaires about the content to 12 experts. The third step was the revision of the algorithm. The fourth and last step was to establish the clinical validity of the algorithm with 25 experienced nurses. Results: For the ease of the practitioner the algorithm for prevention and the management of pressure ulcers was confined to one page depicting the main algorithm pathway and seven stepwise guidelines. The guidelines included skin care of pressure ulcer prevention, mechanical loading care, support surface care, reposition care of pressure ulcer, and Stages II, III and IV explanations along with debridement/wound irrigation and infection control. Most of all algorithm courses chosen more than 80% of agreement by expert index of content validity. The usefulness, appropriateness, and convenience of the algorithm were demonstrated through clinical validity with intensive care unit and ward nurses. Conclusion: The algorithm will improve the quality of pressure ulcer nursing care as it provides a model for decision making for clinical nurses as well as providing consistent and integrated nursing care for patients with pressure ulcer throughout an institution.

Software Key Node Recognition Algorithm for Defect Detection based on Node Expansion Degree and Improved K-shell Position

  • Wanchang Jiang;Zhipeng Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권7호
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    • pp.1817-1839
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    • 2024
  • To solve the problem of insufficient recognition of key nodes in the existing software defect detection process, this paper proposes a key node recognition algorithm based on node expansion degree and improved K-shell position, shortened as SDD_KNR. Firstly, the calculation formula of node expansion degree is designed to improve the degree that can measure the local defect propagation capability of nodes in the software network. Secondly, the concept of improved K-shell position of node is proposed to obtain the improved K-shell position of each node. Finally, the measurement of node defect propagation capability is defined, and the key node recognition algorithm is designed to identify the key function nodes with large defect impact range in the process of software defect detection. Using real software systems such as Nano, Cflow and Tar to design three sets of experiments. The corresponding directed weighted software function invoke networks are built to simulate intentional attack and defect source infection. The proposed SDD_KNR algorithm is compared with the BC algorithm, K-shell algorithm, KNMWSG algorithm and NMNC algorithm. The changing trend of network efficiency and the strength of node propagation force are analyzed to verify the effectiveness of the proposed SDD_KNR algorithm.

K-평균 군집화 알고리즘 및 딥러닝 기반 군중 집계를 이용한 전염병 확진자 접촉 가능성 여부 판단 모니터링 시스템 제안 (Proposal of a Monitoring System to Determine the Possibility of Contact with Confirmed Infectious Diseases Using K-means Clustering Algorithm and Deep Learning Based Crowd Counting)

  • 이동수;;김영광;신혜주;김진술
    • 스마트미디어저널
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    • 제9권3호
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    • pp.122-129
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    • 2020
  • 전 세계적으로 무증상의 코로나바이러스 감염증-19 감염자가 자신이 감염된 것을 모르고 주변인들에게 전파할 수 있다는 가능성은 국민이 전염병 확산에 대한 불안과 두려움에서 벗어나지 못하고 있다는 점에서 여전히 매우 중요한 이슈이다. 본 논문에서는 K-평균 군집화 알고리즘 및 딥러닝 기반 군중 집계를 이용한 전염병 확진자 접촉 가능성 여부 판단 모니터링 시스템을 제안하였다. 모든 입력 학습 영상에 대해 300회 반복 학습한 결과, PSNR값은 21.51, 전체 데이터 셋에 대한 최종 MAE값은 67.984였다. 이는 확진자와 주변인과의 거리와 감염률 산출, 잠재적 환자 동선 주변 인원의 위험도 순 그룹 및 감염률 예측에 대한 영상 속 화질 정보, 관측치 간의 평균 절대 오차를 의미하며 각 CCTV 장면에서 군중의 수가 4,000명 이하일 때에는 평균 절대 오차 값이 0에 가까움을 증명하였다.

The potential of non-movement behavior observation method for detection of sick broiler chickens

  • Hyunsoo Kim;Woo-Do Lee;Hyung-Kwan Jang;Min Kang;Hwan-Ku Kang
    • Journal of Animal Science and Technology
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    • 제65권2호
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    • pp.441-458
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    • 2023
  • The poultry industry, which produces excellent sources of protein, suffers enormous economic damage from diseases. To solve this problem, research is being conducted on the early detection of infection according to the behavioral characteristics of poultry. The purpose of this study was to evaluate the potential of a non-movement behavior observation method to detect sick chickens. Forty 1-day-old Ross 308 males were used in the experiments, and an isolator equipped with an Internet Protocol (IP) camera was fabricated for observation. The chickens were inoculated with Salmonella enterica serovar Gallinarum A18-GCVP-014, the causative agent of fowl typhoid (FT), at 14 days of age, which is a vulnerable period for FT infection. The chickens were continuously observed with an IP camera for 2 weeks after inoculation, chickens that did not move for more than 30 minutes were detected and marked according to the algorithm. FT infection was confirmed based on clinical symptoms, analysis of cardiac, spleen and liver lesion scores, pathogen re-isolation, and serological analysis. As a result, clinical symptoms were first observed four days after inoculation, and dead chickens were observed on day six. Eleven days after inoculation, the number of clinical symptoms gradually decreased, indicating a state of recovery. For lesion scores, dead chickens scored 3.57 and live chickens scored 2.38. Pathogens were re-isolated in 37 out of 40 chickens, and hemagglutination test was positive in seven out of 26 chickens. The IP camera applied with the algorithm detected about 83% of the chickens that died in advance through non-movement behavior observation. Therefore, observation of non-movement behavior is one of the ways to detect infected chickens in advance, and it appears to have potential for the development of remote broiler management system.