• Title/Summary/Keyword: predictive ability

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Predictive analyses for balance and gait based on trunk performance using clinical scales in persons with stroke

  • Woo, Youngkeun
    • Physical Therapy Rehabilitation Science
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    • v.7 no.1
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    • pp.29-34
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    • 2018
  • Objective: This study aimed to predict balance and gait abilities with the Trunk Impairment scales (TIS) in persons with stroke. Design: Cross-sectional study. Methods: Sixty-eight participants with stoke were assessed with the TIS, Berg Balance scale (BBS), and Functional Gait Assessment (FGA) by a therapist. To describe of general characteristics, we used descriptive and frequency analyses, and the TIS was used as a predictive variable to determine the BBS. In the simple regression analysis, the TIS was used as a predictive variable for the BBS and FGA, and the TIS and BBS were used as predictive variables to determine the FGA in multiple regression analysis. Results: In the group with a BBS score of >45 for regression equation for predicting BBS score using TIS score, the coefficient of determination ($R^2$) was 0.234, and the $R^2$ was 0.500 in the group with a BBS score of ${\leq}45$. In the group with an FGA score >15 for regression equation for predicting FGA score using TIS score, the $R^2$ was 0.193, and regression equation for predicting FGA score using TIS score, the $R^2$ was 0.181 in the group of FGA score ${\leq}15$. In the group of FGA score >15 for regression equation for predicting FGA score using TIS and BBS score, the $R^2$ was 0.327. In the group of FGA score ${\leq}15$ for regression equation for predicting FGA score using TIS and BBS score, the $R^2$ was 0.316. Conclusions: The TIS scores are insufficient in predicting the FGA and BBS scores in those with higher balance ability, and the BBS and TIS could be used for predicting variables for FGA. However, TIS is a strong predictive variable for persons with stroke who have poor balance ability.

Comparative Molecular Field Analysis of Caspase-3 Inhibitors

  • Sathya, B.;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.7 no.3
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    • pp.166-172
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    • 2014
  • Caspases, a family of cysteinyl aspartate-specific proteases plays a central role in the regulation and the execution of apoptotic cell death. Activation of caspases-3 stimulates a signaling pathway that ultimately leads to the death of the cell. Hence, caspase-3 has been proven to be an effective target for reducing the amount of cellular and tissue damage. In this work, comparative molecular field analysis (CoMFA) was performed on a series of 3, 4-dihydropyrimidoindolones derivatives which are inhibitors of caspase-3. The best predictions were obtained for CoMFA model ($q^2=0.676$, $r^2=0.990$). The predictive ability of test set ($r^2_{pred}$) was 0.688. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. Our theoretical results could be useful to design novel and more potent caspase-3 derivatives.

Comparative Molecular Similarity Indices Analysis of Caspase-3 Inhibitors

  • Babu, Sathya;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.7 no.4
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    • pp.227-233
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    • 2014
  • Caspases, a family of cysteinyl aspartate-specific proteases plays a central role in the regulation and the execution of apoptotic cell death. Activation of caspases-3 stimulates a signaling pathway that ultimately leads to the death of the cell. Hence, caspase-3 has been proven to be an effective target for reducing the amount of cellular and tissue damage. In this work, comparative molecular similarity indices analysis (CoMSIA) was performed on a series of 3,4-dihydropyrimidoindolones derivatives which are inhibitors of caspase-3. The best predictions were obtained for CoMSIA model ($q^2$ = 0.586, $r^2$ = 0.955). The predictive ability of test set ($r^2_{pred}$) was 0.723. Statistical parameters from the generated QSAR models indicated the data is well fitted and have high predictive ability. Our theoretical results could be useful to design novel and more potent caspase-3 derivatives.

Predictors of Preschoolers' Reading Skills : Analysis by Age Groups and Reading Tasks (유아의 단어읽기 능력 예측변수 : 연령 집단별, 단어 유형별 분석)

  • Choi, Na-Ya;Yi, Soon-Hyung
    • Journal of Families and Better Life
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    • v.26 no.4
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    • pp.41-54
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    • 2008
  • The purpose of this study was to investigate predictors concerning preschoolers' ability to read words, in terms of their sub-skills of alphabet knowledge, phonological awareness, and phonological processing. Fourteen literacy sub-tests and three types of reading tasks were administered to 289 kindergartners aged 4 to 6 in Busan. The main results are as follows. Sub-skills that predicted reading ability varied with children's age. Irrespective of children's age groups, knowledge of consonant names and digit naming speed commonly explained the reading of real words. In contrast, skills of syllable deletion and phoneme substitution and knowledge of alphabet composition principles were related to only 4-year-olds' reading skills. Exclusively included was digit memory in predicting 5-year-olds' reading abilities, and knowledge of vowel sounds in 6-year-olds' reading skills. The type of reading task also influenced reading ability. A few common variables such as knowledge of consonant names and vowel sounds, digit naming speed, and phoneme substitution skill explained all types of word reading. Syllable counting skills, however, had predictive value only for the reading of real words. Phoneme insertion skills and digit memory had predictive value for the reading of pseudo words and low frequency letters. Likewise, knowledge of consonant sounds and vowel stroke-adding principles were significant only for the reading of low frequency letters.

Premature Ejaculation and Erectile Dysfunction in Iranian Prostate Cancer Patients

  • Lin, Chung-Ying;Burri, Andrea;Pakpour, Amir H
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.4
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    • pp.1961-1966
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    • 2016
  • Background: To investigate the prevalence of premature ejaculation (PE) and erectile dysfunction (ED) in a sample of patients with prostate cancer and to determine the utility of the previously suggested cutoffs of the Premature Ejaculation Diagnostic Tool (PEDT) for the diagnosis of PE and that of International Index of Erectile Function (IIEF-5) for ED. Materials and Methods: A total of 1,202 men with prostate cancer were invited from urology clinics at the universities of Iran, Tehran, Qazvin, Ahvaz, Guilan and Tabriz. Clinical characteristics were collected through medical records. PE and ED diagnoses were made by trained urologists. In addition to the clinical diagnoses, PE and ED were measured through self-report using the PEDT and the IIEF-5. Questionnaire cutoff scores were determined using receiver operating characteristic (ROC) curves and confirmed by predictive ability using logistic regression. Results: The prevalence of PE was 63.7% and that of ED was 66.2%. Prevalences of PE decreased and that of ED increased with advanced TNM stages. According to ROC, the suggested cutoff for the PEDT to diagnose a PE was ${\geq}11$ (sensitivity=0.988, 1-specificity=0.084, and predictive ability=0.914) and ${\leq}17$ for the IIEF-5 (sensitivity=0.966, 1-specificity=0.031, and predictive ability=0.967). Conclusions: Prevalence of sexual problems was high in prostate cancer patients in Iran, therefore oncologists should take into account these potential problems when deciding on treatment modalities.

The Relationship of Home Environments to Children's Social Development : Analysis of a Causal Model (가정환경변인과 아동의 사회적 능력간의 관계 : 인과 모형 분석)

  • Jang, Young Ae
    • Korean Journal of Child Studies
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    • v.8 no.2
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    • pp.17-44
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    • 1987
  • The study examined the characteristics of the relationship of home environment variables and children's social development. Two studies were conducted ; Study I examined (1) the correlation of home environment variables and children's social ability and (2) the predictability of home environment variables for children's social ability by children's age. Study II investigated the causal relationship among the variables which are supposed to affect children's social ability. The subjects of this study were 240 children at age four, six and eight attending nursery schools, kindergartens and elementary schools and their mothers. Instruments included the Inventory of Home Stimulation (HOME), the Inventory of Sociodemographic Variables, social maturation scale, and the social-emotional developmental rating scale. The results obtained from this study were as follows : 1) Home environment variables had a positive correlation with children's social development at age four and six, but at age eight, only HOME variables had a significant positive correlation with children's social development. 2) The home environmental variables that significantly predicted children's social development differed according to children's age. That is, play materials, economic status of the home, and parent education were predictive of children's social development at age four, while parent's education, fostering maturity and independence, and play materials were predictive at age six. Fostering maturity and independence, aspects of physical environment, and economic status of the home were predictive at age eight. 3) The causal model of home environment effect on children's social development was formulated by exogenous variables (parent education and economic status of the home) and endogenous variables (direct stimulation, indirect stimulation and the emotional climate of the home). 4) The results of the analysis of the causal model showed that the variables that have a direct effect on children's social development differed according to children's age. That is, direct stimulation had more effect on children's social development at earlier ages, and indirect stimulation had more effect on children's social development at later ages. Among socio-demographic variables, parent's education was most closely related to children's social development. The amount of variance that explained children's social development decreased with increase in children's age.

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Predicting Economic Activity via the Yield Spread: Literature Survey and Empirical Evidence in Korea (이자율 스프레드의 경기 예측력: 문헌 서베이 및 한국의 사례 분석)

  • Yun, Jaeho
    • Economic Analysis
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    • v.26 no.3
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    • pp.1-47
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    • 2020
  • This paper surveys research since the 1990s on the ability of the yield spread and its components (i.e., expectation spread and term premium components) for future economic activity, and also conducts an empirical analysis of their forecasting ability using the yield data of Korean government bonds. This paper's survey, particularly for the US, shows that the yield spread has significant predictive power for some macroeconomic variables, but since the mid-1980s, its predictive power seems to have declined, possibly due to stronger inflation targeting. Next, this paper's empirical analysis using Korean data indicates that the yield spread, and the term premium component in particular, has significant predictive power for industrial production (IP) growth, consumer price index growth, and the IP gap. An out-of-sample analysis shows that the prediction equations are unstable over time, and that in predicting IP growth, the yield spread decomposition makes a significant contribution to the prediction of IP growth.

Predictive modeling algorithms for liver metastasis in colorectal cancer: A systematic review of the current literature

  • Isaac Seow-En;Ye Xin Koh;Yun Zhao;Boon Hwee Ang;Ivan En-Howe Tan;Aik Yong Chok;Emile John Kwong Wei Tan;Marianne Kit Har Au
    • Annals of Hepato-Biliary-Pancreatic Surgery
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    • v.28 no.1
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    • pp.14-24
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    • 2024
  • This study aims to assess the quality and performance of predictive models for colorectal cancer liver metastasis (CRCLM). A systematic review was performed to identify relevant studies from various databases. Studies that described or validated predictive models for CRCLM were included. The methodological quality of the predictive models was assessed. Model performance was evaluated by the reported area under the receiver operating characteristic curve (AUC). Of the 117 articles screened, seven studies comprising 14 predictive models were included. The distribution of included predictive models was as follows: radiomics (n = 3), logistic regression (n = 3), Cox regression (n = 2), nomogram (n = 3), support vector machine (SVM, n = 2), random forest (n = 2), and convolutional neural network (CNN, n = 2). Age, sex, carcinoembryonic antigen, and tumor staging (T and N stage) were the most frequently used clinicopathological predictors for CRCLM. The mean AUCs ranged from 0.697 to 0.870, with 86% of the models demonstrating clear discriminative ability (AUC > 0.70). A hybrid approach combining clinical and radiomic features with SVM provided the best performance, achieving an AUC of 0.870. The overall risk of bias was identified as high in 71% of the included studies. This review highlights the potential of predictive modeling to accurately predict the occurrence of CRCLM. Integrating clinicopathological and radiomic features with machine learning algorithms demonstrates superior predictive capabilities.

A neural-based predictive model of the compressive strength of waste LCD glass concrete

  • Kao, Chih-Han;Wang, Chien-Chih;Wang, Her-Yung
    • Computers and Concrete
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    • v.19 no.5
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    • pp.457-465
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    • 2017
  • The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.

Evaluating Geomorphological Classification Systems to Predict the Occurrence of landslides in Mountainous Region (산사태 발생예측을 위한 지형분류기법의 비교평가)

  • Lee, Sooyoun;Jeong, Gwanyong;Park, Soo Jin
    • Journal of the Korean Geographical Society
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    • v.50 no.5
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    • pp.485-503
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    • 2015
  • This study aims at evaluating geomorphological classification systems to predict the occurrence of landslides in mountainous region in Korea. Geomorphological classification systems used in this study are Catena, TPI, and Geomorphons. Study sites are Gapyeong-gun, Hoengseong-gun, Gimcheon-si, Yeoju-si/Yicheon-si in which landslide occurrence data were collected by local governments from 2001-2014. Catena method has objective classification standard to compare among regions objectively and understand the result intuitively. However, its procedure is complicated and hard to be automated for the general public to use it. Both TPI and Geomorphons have simple procedure and GIS-extension, therefore it has high accessibility. However, the results of both systems are highly dependent on the scale, and have low relevance to geomorphological formation process because focusing on shape of terrain. Three systems have low compatibility, therefore unified concept are required for broad use of landform classification. To assess the effectiveness of prediction on landslide by each geomorphological classification system, 50% of geomorphological classes with higher landslide occurrence are selected and the total landslide occurrence in selected classes are calculated and defined as 'predictive ability'. The ratio of terrain categorized by 'predictive ability' to whole region is defined as 'vulnerable area ratio'. An indicator to compare three systems which is predictive ability divided by vulnerable area ratio was developed to make a comprehensive judgment. As a result, Catena ranked the highest in suitability.

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