• 제목/요약/키워드: Receiver sensitivity

검색결과 592건 처리시간 0.033초

Aberrant Methylation of Genes in Sputum Samples as Diagnostic Biomarkers for Non-small Cell Lung Cancer: a Meta-analysis

  • Wang, Xu;Ling, Li;Su, Hong;Cheng, Jian;Jin, Liu
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권11호
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    • pp.4467-4474
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    • 2014
  • Background: We aimed to comprehensively review the evidence for using sputum DNA to detect non-small cell lung cancer (NSCLC). Materials and Methods: We searched PubMed, Science Direct, Web of Science, Chinese Biological Medicine (CBM), Chinese National Knowledge Infrastructure (CNKI), Wanfang, Vip Databases and Google Scholar from 2003 to 2013. The meta-analysis was carried out using a random-effect model with sensitivity, specificity, diagnostic odd ratios (DOR), summary receiver operating characteristic curves (ROC curves), area under the curve (AUC), and 95% confidence intervals (CI) as effect measurements. Results: There were twenty-two studies meeting the inclusion criteria for the meta-analysis. Combined sensitivity and specificity were 0.62 (95%CI: 0.59-0.65) and 0.73 (95%CI: 0.70-0.75), respectively. The DOR was 10.3 (95%CI: 5.88-18.1) and the AUC was 0.78. Conclusions: The overall accuracy of the test was currently not strong enough for the detection of NSCLC for clinical application. Dscovery and evaluation of additional biomarkers with improved sensitivity and specificity from studies rated high quality deserve further attention.

Reconsideration of F1 Score as a Performance Measure in Mass Spectrometry-based Metabolomics

  • Jeong, Jaesik;Kim, Han Sol;Kim, Shin June
    • 통합자연과학논문집
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    • 제11권3호
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    • pp.161-164
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    • 2018
  • Over the past decade, mass spectrometry-based metabolomics, especially two dimensional gas chromatography mass spectrometry (GCxGC/TOF-MS), has become a key analytical tool for metabolomics data because of its sensitivity and ability to analyze complex biological or biochemical sample. However, the need to reduce variations within/between experiments has been reported and methodological developments to overcome such problem has long been a critical issue. Along with methodological developments, developing reasonable performance measure has also been studied. Following four numerical measures have been typically used for comparison: sensitivity, specificity, receiver operating characteristic (ROC) curves, and positive predictive value (PPV). However, more recently, such measures are replaced with F1 score in many fields including metabolomics area without any carefulness of its validity. Thus, we want to investigate the validity of F1 score on two examples, with the goal of raising the awareness in choosing appropriate performance comparison measure. We noticed that F1 score itself, as a performance measure, was not good enough. Accordingly, we suggest that F1 score be supplemented with other performance measure such as specificity to improve its validity.

Diagnostic value of eosinopenia and neutrophil to lymphocyte ratio on early onset neonatal sepsis

  • Wilar, Rocky
    • Clinical and Experimental Pediatrics
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    • 제62권6호
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    • pp.217-223
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    • 2019
  • Purpose: To determine the diagnostic value of eosinopenia and the neutrophil-to-lymphocyte ratio (NLR) in the diagnosis of early onset neonatal sepsis (EONS). Methods: This cross-sectional study was conducted in the Neonatology Ward of R.D. Kandou General Hospital Manado between July and October 2017. Samples were obtained from all neonates meeting the inclusion criteria for EONS. Data were encoded using logistic regression analysis, the point-biserial correlation coefficient, chi-square test, and receiver operating characteristic curve analysis, with a P value <0.05 considered significant. Results: Of 120 neonates who met the inclusion criteria, 73 (60.8%) were males and 47 (39.2%) were females. Ninety (75%) were included in the sepsis group and 30 (25%) in the nonsepsis group. The mean eosinophil count in EONS and non-EONS groups was $169.8{\pm}197.1cells/mm^3$ and $405.7{\pm}288.9cells/mm^3$, respectively, with statistically significant difference (P<0.001). The diagnostic value of eosinopenia in the EONS group (cutoff point: $140cells/mm^3$) showed 60.0% sensitivity and 90.0% specificity. The mean NLR in EONS and non-EONS groups was $2.82{\pm}2.29$ and $0.82{\pm}0.32$, respectively, with statistically significant difference (P<0.001). The diagnostic value of NLR in the EONS group (cutoff point, 1.24) showed 83.3% sensitivity and 93.3% specificity. Conclusion: Eosinopenia has high specificity as a diagnostic marker for EONS and an increased NLR has high sensitivity and specificity as a diagnostic marker for EONS.

Meta-analysis of the Diagnostic Test Accuracy of Pediatric Inpatient Fall Risk Assessment Scales

  • Kim, Eun Joo;Lim, Ji Young;Kim, Geun Myun;Lee, Mi Kyung
    • Child Health Nursing Research
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    • 제25권1호
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    • pp.56-64
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    • 2019
  • Purpose: This study was conducted to obtain data for the development of an effective fall risk assessment tool for pediatric inpatients through a systematic review and meta-analysis of the diagnostic test accuracy of existing scales. Methods: A literature search using Medline, Science Direct, CINAHL, EMBASE, and the Cochrane Library was performed between March 1 and 31, 2018. Of 890 identified papers, 10 were selected for review. Nine were used in the meta-analysis. Stata version 14.0 was used to create forest plots of sensitivity and specificity. A summary receiver operating characteristic curve was used to compare all diagnostic test accuracies. Results: Four studies used the Humpty Dumpty Falls Scale. The most common items included the patient's diagnoses, use of sedative medications, and mobility. The pooled sensitivity and specificity of the nine studies were .79 and .36, respectively. Conclusion: Considering the low specificity of the pediatric fall risk assessment scales currently available, there is a need to subdivide scoring categories and to minimize items that are evaluated using nurses' subjective judgment alone. Fall risk assessment scales should be incorporated into the electronic medical record system and an automated scoring system should be developed.

Evaluation of maxillary sinusitis from panoramic radiographs and cone-beam computed tomographic images using a convolutional neural network

  • Serindere, Gozde;Bilgili, Ersen;Yesil, Cagri;Ozveren, Neslihan
    • Imaging Science in Dentistry
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    • 제52권2호
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    • pp.187-195
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    • 2022
  • Purpose: This study developed a convolutional neural network (CNN) model to diagnose maxillary sinusitis on panoramic radiographs(PRs) and cone-beam computed tomographic (CBCT) images and evaluated its performance. Materials and Methods: A CNN model, which is an artificial intelligence method, was utilized. The model was trained and tested by applying 5-fold cross-validation to a dataset of 148 healthy and 148 inflamed sinus images. The CNN model was implemented using the PyTorch library of the Python programming language. A receiver operating characteristic curve was plotted, and the area under the curve, accuracy, sensitivity, specificity, positive predictive value, and negative predictive values for both imaging techniques were calculated to evaluate the model. Results: The average accuracy, sensitivity, and specificity of the model in diagnosing sinusitis from PRs were 75.7%, 75.7%, and 75.7%, respectively. The accuracy, sensitivity, and specificity of the deep-learning system in diagnosing sinusitis from CBCT images were 99.7%, 100%, and 99.3%, respectively. Conclusion: The diagnostic performance of the CNN for maxillary sinusitis from PRs was moderately high, whereas it was clearly higher with CBCT images. Three-dimensional images are accepted as the "gold standard" for diagnosis; therefore, this was not an unexpected result. Based on these results, deep-learning systems could be used as an effective guide in assisting with diagnoses, especially for less experienced practitioners.

Risk Factors of the 2-Year Mortality after Bipolar Hemiarthroplasty for Displaced Femoral Neck Fracture

  • Jung Wook Huh;Han Eol Seo;Dong Ha Lee;Jae Heung Yoo
    • Hip & pelvis
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    • 제35권3호
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    • pp.164-174
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    • 2023
  • Purpose: This study investigates the relationship between preoperative neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-C-reactive protein ratio (LCR), albumin, and 2-year mortality in elderly patients having hemiarthroplasty for displaced femoral neck fracture (FNF). Materials and Methods: We retrospectively reviewed 284 elderly patients who underwent hemiarthroplasty for Garden type IV FNF from September 2014 to September 2020. Using the receiver operating characteristic curve, optimal cutoff values for LCR, NLR, and albumin were established, and patients were categorized as low or high. Associations with 2-year mortality were evaluated through univariate and multivariate Cox regression analyses. Results: Of the 284 patients, 124 patients (45.9%) died within 2 years post-surgery. The optimal cutoff values were: LCR at 7.758 (specificity 58.5%, sensitivity 25.0%), NLR at 3.854 (specificity 39.2%, sensitivity 40.0%), and albumin at 3.750 (specificity 65.9%, sensitivity 21.9%). Patients with low LCR (<7.758), high NLR (≥3.854), and low albumin (<3.750) had a statistically significant reduced survival time compared to their counterparts. Conclusion: Lower preoperative LCR and albumin levels, along with higher NLR, effectively predict 2-year mortality and 30-day post-surgery complications in elderly patients with Garden type IV FNF undergoing hemiarthroplasty.

적외선 체열 촬영을 이용한 안면홍조 진단의 절단값 산정 (The Cut Off Values for Diagnosing Hot flashes by Using Digital Infrared Thermographic Imaging)

  • 조준영;황덕상;이창훈;장준복;이경섭;이진무
    • 대한한방부인과학회지
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    • 제26권3호
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    • pp.85-92
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    • 2013
  • Objectives: The purpose of this study is to find diagnostic points and define the cut off values of hot flashes by using digital infrared thermographic imaging. Methods: Thermographic images of 75 patients with hot flashes (HF, n=35) and non-hot flashes (NHF, n=40) were retrospectively reviewed. We used the temperature difference between Ex-HN3 and CV17, LU4, CV12, CV4 for diagnosing hot flashes. The temperature differences of between two groups were analysed using independent samples t-tests. The cut off values were calculated by received operating characteristic curve analysis. Analyses were undertaken using SPSS version 17.0. and p-value of <0.05 was considered significant. Results: The temperature difference Ex-HN3 and LU4 were the most significantly different between groups (p<0.001). Using receiver operating characteristic curve analysis, the sensitivity, specificity, and area under the curve were 65.7%, 72.5%, 0.729, respectively. The optimum cut off value was defined as $1.00^{\circ}C$. Conclusions: These results suggest that the digital infrared thermographic imaging is a reliable instrument for estimating hot flashes.

데이터 마이닝 결정나무를 이용한 포렌식 영상의 분류 (Forensic Image Classification using Data Mining Decision Tree)

  • 이강현
    • 전자공학회논문지
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    • 제53권7호
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    • pp.49-55
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    • 2016
  • 디지털 포렌식 영상은 여러 가지 영상타입으로 위 변조되어 유통되는 심각한 문제가 대두되어 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 포렌식 영상의 분류 알고리즘을 제안한다. 제안된 알고리즘은 여러 가지 영상타입의 그레이 레벨 co-occurrence 행렬의 특성 중에서 콘트라스트와 에너지 그리고 영상의 엔트로피로 21-dim.의 특징벡터를 추출하고, 결정나무 플랜에서 분류학습을 위하여 PPCA를 이용하여 2-dim.으로 차원을 축소한다. 포렌식 영상의 분류 테스트는 영상 타입들의 전수조합에서 수행되었다. 실험을 통하여, TP (True Positive)와 FN (False Negative)을 검출하고, 제안된 알고리즘의 성능평가에서 민감도 (Sensitivity)와 1-특이도 (1-Specificity)의 AUROC (Area Under Receiver Operating Characteristic) 커브 면적은 0.9980으로 'Excellent(A)' 등급임을 확인하였다. 산출된 최소평균 판정에러 0.0179에서 분류할 포렌식 영상타입이 모두 포함되어 분류 효율성이 높다.

FMCW 송수신 칩을 이용한 단일 안테나 레이다 센서 (Single Antenna Radar Sensor with FMCW Radar Transceiver IC)

  • 유경하;유준영;박명철;어윤성
    • 한국전자파학회논문지
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    • 제29권8호
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    • pp.632-639
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    • 2018
  • 본 논문에서는 130 nm 공정을 이용한 Ku-band에서의 송수신 칩을 사용하여 제작된 단일 안테나 모듈을 제안한다. 레이다 수신부에서 DCOC 피드백을 사용한 STC(sensitivity time control)가 거리에 따라 일정한 SNR을 유지한다. 또한 수신부 RF단에서 gain control을 통하여 수신단의 dynamic range를 조절할 수 있다. 칩의 출력 파워는 9 dBm이고, 수신부의 총 이득은 82 dB이다. 단일 안테나에서 Tx 신호가 Rx로 직접 누설되는 것을 막기 위해 stub-tuned hybrid coupler를 사용하였다. 최대 측정거리는 6 m이고, 혼안테나와 금속판을 사용하여 측정하였다.

위·변조 영상의 에지 에너지 정보를 이용한 영상 포렌식 판정 알고리즘 (Image Forensic Decision Algorithm using Edge Energy Information of Forgery Image)

  • 이강현
    • 전자공학회논문지
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    • 제51권3호
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    • pp.75-81
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    • 2014
  • 디지털 영상의 배포에서, 저작권 침해자에 의해 영상이 불법으로 위 변조되어 유통되는 심각한 문제가 대두되어 있다. 이러한 문제를 해결하기 위하여, 본 논문에서는 위 변조된 디지털 영상의 에지 에너지 정보를 이용한 영상 포렌식 판정 알고리즘을 제안한다. 제안된 알고리즘은 SA (Streaking Artifacts)와 SPAM (Subtractive Pixel Adjacency Matrix)을 이용하여, 원 영상의 JPEG 압축률 (QF=90, 70, 50, 30)에 따른 에지정보와 질의영상의 에지정보를 추출하고, 이를 각각 비교하여 위 변조 여부를 판정한다. 원 영상과 질의영상의 에지정보 매칭은 JPEG 압축률 조합의 임계치 (TCJCR : Threshold by Combination of JPEG Compression Ratios)에 따라 이루어진다. 실험을 통하여, TP (True Positive)와 FN (False Negative)은 87.2%와 13.8%이며, 산출된 최소평균 판정 에러는 0.1349이다. 그리고 제안된 알고리즘의 성능평가에서 민감도 (Sensitivity)와 1-특이도(1-Specificity)의 AUROC (Area Under Receiver Operating Characteristic) 커브 면적은 0.9388로 'Excellent(A)' 등급임을 확인하였다.