• Title/Summary/Keyword: receiver operating characteristic curve

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Selection of markers in the framework of multivariate receiver operating characteristic curve analysis in binary classification

  • Sameera, G;Vishnu, Vardhan R
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.79-89
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    • 2019
  • Classification models pertaining to receiver operating characteristic (ROC) curve analysis have been extended from univariate to multivariate setup by linearly combining available multiple markers. One such classification model is the multivariate ROC curve analysis. However, not all markers contribute in a real scenario and may mask the contribution of other markers in classifying the individuals/objects. This paper addresses this issue by developing an algorithm that helps in identifying the important markers that are significant and true contributors. The proposed variable selection framework is supported by real datasets and a simulation study, it is shown to provide insight about the individual marker's significance in providing a classifier rule/linear combination with good extent of classification.

NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF A CONCAVE RECEIVER OPERATING CHARACTERISTIC CURVE VIA GEOMETRIC PROGRAMMING

  • Lee, Kyeong-Eun;Lim, Johan
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.3
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    • pp.523-537
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    • 2011
  • A receiver operating characteristic (ROC) curve plots the true positive rate of a classier against its false positive rate, both of which are accuracy measures of the classier. The ROC curve has several interesting geometrical properties, including concavity which is a necessary condition for a classier to be optimal. In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) of a concave ROC curve and its modification to reduce bias. We characterize the NPMLE as a solution to a geometric programming, a special type of a mathematical optimization problem. We find that the NPMLE is close to the convex hull of the empirical ROC curve and, thus, has smaller variance but positive bias at a given false positive rate. To reduce the bias, we propose a modification of the NPMLE which minimizes the $L_1$ distance from the empirical ROC curve. We numerically compare the finite sample performance of three estimators, the empirical ROC curve, the NMPLE, and the modified NPMLE. Finally, we apply the estimators to estimating the optimal ROC curve of the variance-threshold classier to segment a low depth of field image and to finding a diagnostic tool with multiple tests for detection of hemophilia A carrier.

A Novel System for Detecting Adult Images on the Internet

  • Park, Jae-Yong;Park, Sang-Sung;Shin, Young-Geun;Jang, Dong-Sik
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.5
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    • pp.910-924
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    • 2010
  • As Internet usage has increased, the risk of adolescents being exposed to adult content and harmful information on the Internet has also risen. To help prevent adolescents accessing this content, a novel detection method for adult images is proposed. The proposed method involves three steps. First, the Image Of Interest (IOI) is extracted from the image background. Second, the IOI is distinguished from the segmented image using a novel weighting mask, and it is determined to be acceptable or unacceptable. Finally, the features (color and texture) of the IOI or original image are compared to a critical value; if they exceed that value then the image is deemed to be an adult image. A Receiver Operating Characteristic (ROC) curve analysis was performed to define this optimal critical value. And, the textural features are identified using a gray level co-occurrence matrix. The proposed method increased the precision level of detection by applying a novel weighting mask and a receiver operating characteristic curve. To demonstrate the effectiveness of the proposed method, 2850 adult and non-adult images were used for experimentation.

Analysis of SEER Adenosquamous Carcinoma Data to Identify Cause Specific Survival Predictors and Socioeconomic Disparities

  • Cheung, Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.1
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    • pp.347-352
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    • 2016
  • Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) adenosquamous carcinoma data to identify predictive models and potential disparities in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for adenosquamous carcinoma. For the risk modeling, each factor was fitted by a generalized linear model to predict the cause specific survival. An area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: A total of 20,712 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 54.2 (78.4) months. Some 2/3 of the patients were female. The mean (S.D.) age was 63 (13.8) years. SEER stage was the most predictive factor of outcome (ROC area of 0.71). 13.9% of the patients were un-staged and had risk of cause specific death of 61.3% that was higher than the 45.3% risk for the regional disease and lower than the 70.3% for metastatic disease. Sex, site, radiotherapy, and surgery had ROC areas of about 0.55-0.65. Rural residence and race contributed to socioeconomic disparity for treatment outcome. Radiotherapy was underused even with localized and regional stages when the intent was curative. This under use was most pronounced in older patients. Conclusions: Anatomic stage was predictive and useful in treatment selection. Under-staging may have contributed to poor outcome.

Optimization of Predictors of Ewing Sarcoma Cause-specific Survival: A Population Study

  • Cheung, Min Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.10
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    • pp.4143-4145
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    • 2014
  • Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

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

  • Jo, Jun-Young;Hwang, Deok-Sang;Lee, Chang-Hoon;Jang, Jun-Bock;Lee, Kyung-Sub;Lee, Jin-Moo
    • The Journal of Korean Obstetrics and Gynecology
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    • v.26 no.3
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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.

Poor Treatment Outcome of Neuroblastoma and Other Peripheral Nerve Cell Tumors May be Related to Under Usage of Radiotherapy and Socio-Economic Disparity: A US SEER Data Analysis

  • Cheung, Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.9
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    • pp.4587-4592
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    • 2012
  • Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) neuroblastoma (NB) and other peripheral nerve cell tumors (PNCT) outcome data. This study found under usage of radiotherapy in these patients. Materials and methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for NB and other PNCT. For the risk modeling, each factor was fitted by a generalized linear model to predict the outcome (soft tissue specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of neuroendocrine (other endocrine including thymus as coded in SEER) death was computed for the predictors. Results: There were 5261 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 83.8 (97.6) months. The mean (SD) age was 18 (25) years. About 30.45% of patients were un-staged. The SEER staging has high ROC (SD) area of 0.58 (0.01) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged/others) to a simpler 3-tiered model with comparable ROC area of 0.59 (0.01). Less than 50% of PNCT patients received radiotherapy (RT) including the ones with localized disease. This avoidance of RT use occurred in adults and children. Conclusion: The high under-staging rate may have precented patients from selecting definitive radiotherapy (RT) after surgery. Using RT for, especially, adult PNCT patients is a potential way to improve outcome.

Surveying and Optimizing the Predictors for Ependymoma Specific Survival using SEER Data

  • Cheung, Min Rex
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.2
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    • pp.867-870
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    • 2014
  • Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison. Results: A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery. Conclusion: Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.