• Title/Summary/Keyword: infection algorithm

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

  • Park, Yeon-Hwan;Lee, Seong Hyeon;Yi, Yu Mi;Lee, Chi Young;Lee, Min Hye
    • Journal of muscle and joint health
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    • v.25 no.2
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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.

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

  • Park, Jeong-Hyeon;Lee, Sung-Keun;Koh, Jin-Gwang
    • The Journal of Bigdata
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    • v.1 no.1
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    • pp.19-22
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    • 2016
  • Many Studies have been actively conducted on the early diagnosis of the crop pest utilizing IT technology. The purpose of the paper is to discuss on the image processing method capable of detecting the crop leaf pest prematurely by analyzing the image of the leaf received from the camera sensor. This paper proposes an algorithm of diagnosing leaf infection by utilizing an improved K means clustering method. Leaf infection grouping test showed that the proposed algorithm illustrated a better performance in the qualitative evaluation.

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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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    • v.39 no.6
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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
    • Proceedings of the Korean Statistical Society Conference
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    • 2004.11a
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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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    • v.19 no.3
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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.

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

  • Jun, Jae-Min;Seo, Kyu-Tae;Lee, Bo-Hee;Lee, In-Koo;Min, Seung-Ki;Kim, Hak-Jun
    • Proceedings of the KIEE Conference
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    • 2004.11c
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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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Development of an Algorithm for the Prevention and Management of Pressure Ulcers (입원 환자의 욕창예방과 중재를 위한 알고리즘 개발)

  • Kim, Jin-Mi;Park, Jeong-Sook
    • Korean Journal of Adult Nursing
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    • v.22 no.4
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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.

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 (K-평균 군집화 알고리즘 및 딥러닝 기반 군중 집계를 이용한 전염병 확진자 접촉 가능성 여부 판단 모니터링 시스템 제안)

  • Lee, Dongsu;ASHIQUZZAMAN, AKM;Kim, Yeonggwang;Sin, Hye-Ju;Kim, Jinsul
    • Smart Media Journal
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    • v.9 no.3
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    • pp.122-129
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    • 2020
  • The possibility that an asymptotic coronavirus-19 infected person around the world is not aware of his infection and can spread it to people around him is still a very important issue in that the public is not free from anxiety and fear over the spread of the epidemic. In this paper, the K-means clustering algorithm and deep learning-based crowd aggregation were proposed to determine the possibility of contact with confirmed cases of infectious diseases. As a result of 300 iterations of all input learning images, the PSNR value was 21.51, and the final MAE value for the entire data set was 67.984. This means the average absolute error between observations and the average absolute error of fewer than 4,000 people in each CCTV scene, including the calculation of the distance and infection rate from the confirmed patient and the surrounding persons, the net group of potential patient movements, and the prediction of the infection rate.

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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    • v.65 no.2
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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.

Adaptation of Evidence-based Surgical Wound Care Algorithm

  • Han, Jung-Yeon;ChoiKwon, Smi
    • Journal of Korean Academy of Nursing
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    • v.41 no.6
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    • pp.768-779
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    • 2011
  • Purpose: This study was designed to adapt a surgical wound care algorithm that is used to provide evidence-based surgical wound care in a critical care unit. Methods: This study used, the 'ADAPTE process', an international clinical practice guideline development method. The -'Bonnie Sue wound care algorithm' - was used as a draft for the new algorithm. A content validity index (CVI) targeting 135 critical care nurses was conducted. A 5-point Likert scale was applied to the CVI test using a statistical criterion of .75. Results: A surgical wound care algorithm comprised 9 components: wound assessment, infection control, necrotic tissue management, wound classification by exudates and depths, dressing selection, consideration of systemic factors, wound expected outcome, reevaluate non-healing wounds, and special treatment for non-healing wounds. All of the CVI tests were ${\leq}$.75. Compared to existing wound care guidelines, the new wound care algorithm provides precise wound assessment, reliabilities of wound care, expands applicability of wound care to critically ill patients, and provides evidence and strength of recommendations. Conclusion: The new surgical wound care algorithm will contribute to the advancement of evidence-based nursing care, and its use is expected as a nursing intervention in critical care.