Nonparametric inference of the area under ROC curve under two-phase cluster sampling

2021 ◽  
pp. 1-10
Author(s):  
Yougui Wu
Keyword(s):  
Roc Curve ◽  
Nonparametric Inference ◽  
Cluster Sampling ◽  
Two Phase ◽  
Phase Cluster ◽  
Area Under Roc Curve

scholarly journals Parsing Expression Grammars and Their Induction Algorithm

2020 ◽  
Vol 10 (23) ◽  
pp. 8747
Author(s):  
Wojciech Wieczorek ◽  
Olgierd Unold ◽  
Łukasz Strąk
Keyword(s):  
Genetic Programming ◽  
Roc Curve ◽  
Classification Performance ◽  
Grammatical Inference ◽  
Inference Algorithm ◽  
Finite Sample ◽  
Induction Method ◽  
Grammar Learning ◽  
Area Under Roc Curve ◽  
Inference Methods

Grammatical inference (GI), i.e., the task of finding a rule that lies behind given words, can be used in the analyses of amyloidogenic sequence fragments, which are essential in studies of neurodegenerative diseases. In this paper, we developed a new method that generates non-circular parsing expression grammars (PEGs) and compares it with other GI algorithms on the sequences from a real dataset. The main contribution of this paper is a genetic programming-based algorithm for the induction of parsing expression grammars from a finite sample. The induction method has been tested on a real bioinformatics dataset and its classification performance has been compared to the achievements of existing grammatical inference methods. The evaluation of the generated PEG on an amyloidogenic dataset revealed its accuracy when predicting amyloid segments. We show that the new grammatical inference algorithm achieves the best ACC (Accuracy), AUC (Area under ROC curve), and MCC (Mathew’s correlation coefficient) scores in comparison to five other automata or grammar learning methods.

scholarly journals Neonatal Sepsis-Early detection comparing Procalcitonin and CRP as Markers and Newer Tools

2016 ◽  
Vol 5 (1) ◽  
pp. 1048
Author(s):  
Altaf Ahmad Bhat ◽  
Anjum Shamim ◽  
Sabeeha Gul ◽  
Rukaya Akther ◽  
Iqra Bhat
Keyword(s):  
Early Detection ◽  
Roc Curve ◽  
Neonatal Sepsis ◽  
Individual Performance ◽  
Hematological Parameter ◽  
Total Leukocyte Count ◽  
P Value ◽  
Predictive Values ◽  
Maternal Risk ◽  
Area Under Roc Curve

<strong>Background:</strong>Neonatal sepsis continues to be a major cause of morbidity and mortality in India, but is treatable if diagnosis is made in time.<p><strong>Objectives:</strong> The present study was undertaken to evaluate and highlight the importance of procalcitonin v\s CRP in early detection of neonatal sepsis.</p><p><strong>Materials and Methods:</strong> The prospective study enrolled 150 neonates who had maternal risk factors and clinically suspected of infection (study group). Abnormal total leukocyte count, abnormal total polymorphonuclear neutrophils (PMN) count, elevated immature PMN count, elevated immature: Total (I:T) PMN ratio, platelet count ≤150,000/mm3, and pronounced degenerative or toxic changes in PMN were noted by the pathologist who were blind for the clinical status of the baby in NICU. Blood culture was taken as a gold standard for septicemia. The perinatal history, clinical profile and laboratory data were recorded and correlated in each case. Each hematological parameter was assessed for its individual performance and also with the culture-proven sepsis. Sensitivity, specificity, positive and negative predictive values (NPVs) were calculated for each parameter and for different gestational ages. P value was also calculated for different parameters.</p><p><strong>Results:</strong> Among 150 babies evaluated for sepsis in NICU over a period of one year, Procalcitonin is observed as better early marker of neonatal sepsis over and CRP:- Procalcitonin in comparison with CRP: - Sensitivity was 97% Specificity was 59% PPV was 70% and NPV was 99.9%. With area under ROC curve being 0.915(p-value of 0.02) CRP in comparison with Procalcitonin: - Sensitivity was 75% Specificity was 75% PPV was 86% and NPV was 99%. With area under ROC curve being 0.769 (p- value 0.61).</p><p><strong>Conclusion:</strong> The sensitivities of the screening test namely C-reactive protein and Procalcitonin were found to be satisfactory in identifying neonatal sepsis. Comparing to Other test procalcitonin appears to be simple and feasible diagnostic tool although costly.</p>

scholarly journals The value of corticotropin-releasing hormone (CRH) test for differential diagnosis of Cushing’s syndrome

2007 ◽  
Vol 135 (1-2) ◽  
pp. 31-37 ◽  
Author(s):  
Zorana Penezic ◽  
Milos Zarkovic ◽  
Svetlana Vujovic ◽  
Miomira Ivovic ◽  
Biljana Beleslin ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Roc Curve ◽  
Acth Secretion ◽  
Ectopic Acth ◽  
Ectopic Acth Secretion ◽  
Test Sensitivity ◽  
Basal Cortisol ◽  
Area Under Roc Curve ◽  
Curve Method ◽  
Acth Secreting

Introduction: Diagnosis and differential diagnosis of Cushing?s syndrome (CS) remain considerable challenge in endocrinology. For more than 20 years, CRH has been widely used as differential diagnostic test. Following the CRH administration, the majority of patients with ACTH secreting pituitary adenoma show a significant rise of plasma cortisol and ACTH, whereas those with ectopic ACTH secretion characteristically do not. Objective The aim of our study was to assess the value of CRF test for differential diagnosis of CS using the ROC (receiver operating characteristic) curve method. Method A total of 30 patients with CS verified by pathological examination and postoperative testing were evaluated. CRH test was performed within diagnostic procedures. ACTH secreting pituitary adenoma was found in 18, ectopic ACTH secretion in 3 and cortisol secreting adrenal adenoma in 9 of all patients with CS. Cortisol and ACTH were determined -15, 0, 15, 30, 45, 60, 90 and 120 min. after i.v. administration of 100?g of ovine CRH. Cortisol and ACTH were determined by commercial RIA. Statistical data processing was done by ROC curve analysis. Due to small number, the patients with ectopic ACTH secretion were excluded from test evaluation by ROC curve method. Results In evaluated subgroups, basal cortisol was (1147.3?464.3 vs. 1589.8?296.3 vs. 839.2?405.6 nmol/L); maximal stimulated cortisol (1680.3?735.5 vs. 1749.0?386.6 vs. 906.1?335.0 nmol/L); and maximal increase as a percent of basal cortisol (49.1?36.9 vs. 9.0?7.6 vs. 16.7?37.3 %). Consequently, basal ACTH was (100.9 ?85.0 vs. 138.0?123.7 vs. 4.8?4.3 pg/mL) and maximal stimulated ACTH (203.8 ?160.1 vs. 288.0?189.5 vs. 7.4?9.2 pg/mL). For cortisol, determination area under ROC curve was 0.815?0.083 (CI 95% 0.652-0.978). For cortisol increase cut-off level of 20%, test sensitivity was 83%, with specificity of 78%. For ACTH, determination area under ROC curve was 0.637?0.142 (CI 95% 0.359-0.916). For ACTH increase cut-off level of 30%, test sensitivity was 70%, with specificity of 57%. Conclusion Determination of cortisol and ACTH levels in CRH test remains reliable tool in differential diagnosis of Cushing?s syndrome.

scholarly journals Optimal sampling schemes based on the anticipated variance with lack of fit

2002 ◽  
Vol 32 (12) ◽  
pp. 2236-2243 ◽  
Author(s):  
D Mandallaz
Keyword(s):  
Estimation Procedure ◽  
Cluster Sampling ◽  
Second Phase ◽  
Optimal Sampling ◽  
Two Phase ◽  
Sampling Schemes ◽  
Lack Of Fit ◽  
Important Improvement ◽  
Phase Sampling ◽  
Simple Stochastic Model

This note presents an important improvement for optimal sampling schemes based on the anticipated variance. The anticipated variance is defined as the average of the design-based variance under a simple stochastic model in which the trees are assumed to be uniformly and independently distributed within a given number of so-called Poisson strata. We consider two-phase two-stage cluster sampling schemes in which costs and terrestrial second-phase sampling density can vary over domains. The estimation procedure is based on post-stratification with respect to so-called working strata that do not need to be identical with the Poisson strata, usually unknown, which induces a lack of fit. It is then possible to derive analytically the optimal sampling schemes. Data from the Swiss National Inventory illustrates the method.

scholarly journals Partitioning Techniques for Built-In Self-Test Design

VLSI Design ◽  
1994 ◽  
Vol 2 (3) ◽  
pp. 185-198
Author(s):  
Chien-In Henry Chen
Keyword(s):  
Optimal Design ◽  
Design Procedure ◽  
Computationally Efficient ◽  
Two Phase ◽  
Worst Case ◽  
Hardware Overhead ◽  
Phase Cluster ◽  
Unified Algorithm ◽  
Self Test ◽  
Built In Self Test

An efficient, unified algorithm, Advanced Two-Phase Cluster Partitioning, is proposed for automated synthesis of pseudo-exhaustive test generator for Built-In Self-Test (BIST) design. A prototype of the algorithm, Two-Phase Cluster Partitioning, has been proposed and the hierarchical design procedure is computationally efficient and produces test generation circuitry with low hardware overhead. However, in certain worst case, the algorithm may generate a sub-optimal design which requires more test patterns and/or hardware overhead. In order to generate a globally optimal design, further improvement of two-phase algorithm can be achieved by expanding the design space for the formation of linear sum so that the number of test signals required for pseudo-exhaustive testing can be reduced. We demonstrate the effectiveness of our approach by presenting detailed comparisons of our results against those that would be obtained by existing techniques.

Ustekinumab serum concentrations are associated with clinical outcomes in Crohn’s disease – a regional multi-center pilot study

2020 ◽  
Vol 58 (05) ◽  
pp. 439-444 ◽  
Author(s):  
Anne Kerstin Thomann ◽  
Lucas-Alexander Schulte ◽  
Anna-Maria Globig ◽  
Peter Hoffmann ◽  
Thomas Klag ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Pilot Study ◽  
Crohn's Disease ◽  
Clinical Response ◽  
Roc Curve ◽  
Response To Therapy ◽  
Therapeutic Drug ◽  
Serum Concentrations ◽  
Serum Samples ◽  
Area Under Roc Curve

Abstract Background and aim The role of therapeutic drug monitoring (TDM) in ustekinumab (UST) therapy for Crohn’s disease (CD) has not been established, as only few studies have analyzed the relationship between UST serum concentrations and clinical outcome. In this pilot study, we retrospectively examined the potential of UST-concentrations (cUST) 8 weeks after induction (cUSTw8) to predict clinical response at week 16. Methods Serum samples and clinical data from patients (n = 72) with moderate to severely active CD who received intravenous induction with UST were retrospectively analyzed. cUST were quantitated using liquid chromatography-tandem mass spectrometry (LC-MSMS). A receiver-operating characteristic (ROC) curve and area under ROC curve (AUROC) was computed to analyze the predictive potential of cUSTw8 for clinical response at week 16 and to determine the minimal therapeutic UST trough concentration. Results Forty-four patients (61 %) achieved clinical response to UST therapy at week 16. cUSTw8 was moderately effective to predict clinical response with a minimal therapeutic cUSTw8 of 2.0 mg/l (AUC 0.72, p = 0.001). Conclusion Trough concentrations of UST 8 weeks after induction predict clinical response to therapy in week 16 with moderate sensitivity and specificity. TDM using LC-MSMS could prove beneficial in personalized UST therapy of patients with CD by identifying individuals with subtherapeutic concentrations who might benefit from dose escalation.

scholarly journals Detection and Extraction of Weak Pulse Signals in Chaotic Noise with PTAR and DLTAR Models

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Liyun Su ◽  
Li Deng ◽  
Wanlin Zhu ◽  
Shengli Zhao
Keyword(s):  
Roc Curve ◽  
Linear Form ◽  
Hypothesis Test ◽  
Pulse Signal ◽  
Support Vector ◽  
Detector Performance ◽  
Threshold Autoregressive ◽  
Profile Least Squares ◽  
Area Under Roc Curve ◽  
Weak Pulse

With the development in communications, the weak pulse signal is submerged in chaotic noise, which is very common in seismic monitoring and detection of ocean clutter targets, and is very difficult to detect and extract. Based on the threshold autoregressive model, pulse linear form, Markov chain Monte Carlo (MCMC), and profile least squares (PrLS) algorithm, phase threshold autoregressive (PTAR) model and double layer threshold autoregressive (DLTAR) model are proposed for detection and extraction of weak pulse signals in chaotic noise, respectively. Firstly, based on noisy chaotic observation, phase space is reconstructed according to Takens’s delay embedding theorem, and the phase threshold autoregressive (PTAR) model is presented to detect weak pulse signals, and then the MCMC algorithm is applied to estimate parameters in the PTAR model; lastly, we obtain one-step prediction error, which is used to realize adaptively detection of weak signals with the hypothesis test. Secondly, a linear form for the pulse signal and PTAR model is fused to build a DLTAR model to extract weak pulse signals. The DLTAR model owns two kinds of parameters, which are affected mutually. Here, the PrLS algorithm is applied to estimate parameters of the DLTAR model and ultimately extract weak pulse signals. Finally, accurate rate (Acc), receiver operating characteristic (ROC) curve, and area under ROC curve (AUC) are used as the detector performance index; mean square error (MSE), mean absolute percent error (MAPE), and relative error (Re) are used as the extraction accuracy index. The presented scheme does not need prior knowledge of chaotic noise and weak pulse signals, and simulation results show that the proposed PTAR-DLTAR model is significantly effective for detection and extraction of weak pulse signals under chaotic interference. Specifically, in very low signal-to-interference ratio (SIR), weak pulse signals can be detected and extracted compared with support vector machine (SVM) class and neural network model.

scholarly journals Interferon-Gamma Release Assay Performance of Cerebrospinal Fluid and Peripheral Blood in Tuberculous Meningitis in China

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Liping Pan ◽  
Fei Liu ◽  
Jinli Zhang ◽  
Xinting Yang ◽  
Shiqi Zheng ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Tuberculous Meningitis ◽  
Roc Curve ◽  
Peripheral Blood ◽  
Laboratory Tests ◽  
Interferon Gamma Release Assay ◽  
Routine Laboratory ◽  
Assay Performance ◽  
Area Under Roc Curve ◽  
Release Assay

The aim of this study was to examine the performance of T-SPOT.TB on cerebrospinal fluid (CSF) and peripheral blood (PB) in diagnosis of tuberculous meningitis (TBM) in China. Of 100 patients with presumed TBM prospectively enrolled from Sep 2012 to Oct 2014, 53 were TBM (21 definite and 32 probable TBM cases) and 37 were non-TBM cases; the other 10 patients were excluded from analysis due to inconclusive diagnosis, no sufficient CSF samples, or incomplete follow-up. T-SPOT.TB on CSF and PB and routine laboratory tests of CSF were performed simultaneously. The receiver operating characteristic (ROC) curve and cut-off value of CSF T-SPOT.TB and routine CSF parameters were established between TBM and non-TBM group. The area under ROC curve (AUC) of the T-SPOT.TB on CSF and PB was 0.81 and 0.89, which was higher than that of the routine CSF parameters (AUC 0.67–0.77). Although the sensitivity of CSF T-SPOT.TB was lower than that of PB T-SPOT.TB (60.8% versus 90.6%,P<0.001), the specificity of CSF T-SPOT.TB was significantly higher than that of PB T-SPOT.TB (97.2% versus 75.7%,P=0.007). These results indicated that the diagnostic accuracies of PB and CSF T-SPOT.TB are higher than routine laboratory tests. Furthermore, the higher specificity of CSF T-SPOT.TB makes it a useful rule-in test in rapid diagnosis of TBM.

scholarly journals Glycated Albumin Sebagai Penanda Kontrol Glikemik Pada Penderita Diabetes Melitus Tipe 2

2017 ◽  
Vol 1 (1) ◽  
pp. 1-7
Author(s):  
Anselmus Ake ◽  
Made Ratna Saraswati ◽  
I Gde Raka Widiana
Keyword(s):  
Roc Curve ◽  
Glycated Albumin ◽  
Area Under Roc Curve ◽  
Diabetes Melitus

Latar Belakang: Glycated albumin (GA) merupakan indeks kontrol glikemik yang relatif baru. GA mencerminkan statusglukosa darah yang lebih pendek dibandingkan HbA1C, yakni 2-4 minggu sebelumnya. Tujuan: untuk mengetahuiapakah GA dapat digunakan sebagai penanda kontrol glikemik pada penderita DM tipe 2 (DMT2) dengan mencarisensitivitas, spesifisitas, nilai duga positif (NDP), dan nilai duga negatif (NDN) dari GA. Metode: Penelitian inimerupakan uji diagnostik, studi potong lintang, dilaksanakan di RSUP Sanglah dari Desember 2015 hingga Februari2016 menggunakan sampel 59 pasien DMT2. Kontrol glikemik ditentukan dengan HbA1C, glukosa puasa dan glukosa2JPP (baku emas). Hasil: Didapatkan area under ROC curve GA adalah 0,9135 (91,35%). Didapatkan 5 cut off point GAdimana 2 cut off point menunjukkan kemampuan skrining GA yakni ≥18,7% dan ≥19%, 2 cut off point menunjukkankemampuan diagnostik GA yakni ≥21,4% dan 22,4%, dan 1 cut off point optimal yakni 20,4%. Hasil uji diagnostikdengan menggunakan tabel silang 2x2 pada masing-masing cut off point yaitu GA ≥18,7% sensitivitas 94,7%;spesifisitas 76,2%; NDP 87,8%; NDN 88,9%. GA ≥19% sensitivitas 89,5%; spesifisitas 81%; NDP 89,5%; NDN 81%. GA ≥20,4% sensitivitas 81,6%; spesifisitas 85,7%; NDP 91,2%; NDN 72%. GA ≥21,4% sensitivitas 76,3%; spesifisitas 90,5%;NDP 93,5%; NDN 67,9%. GA ≥22,4% sensitivitas 63,2%; spesifisitas 95,2%; NDP 96%; NDN 58,8%. Berdasarkan ujikorelasi, terdapat hubungan positif kuat antara GA dengan HbA1C, GA dengan glukosa puasa dan GA dengan glukosa2JPP. Kesimpulan: Pemeriksaan GA darah dapat digunakan sebagai modalitas diagnostik dalam menilai kontrolglikemik pada penderita DMT2.

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