• 제목/요약/키워드: predictive potential

검색결과 329건 처리시간 0.023초

The Role of Core Needle Biopsy for the Evaluation of Thyroid Nodules with Suspicious Ultrasound Features

  • Sae Rom Chung;Jung Hwan Baek;Young Jun Choi;Tae-Yon Sung;Dong Eun Song;Tae Yong Kim;Jeong Hyun Lee
    • Korean Journal of Radiology
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    • 제20권1호
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    • pp.158-165
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    • 2019
  • Objective: Recent studies demonstrated that core needle biopsy (CNB) can effectively reduce the possibility of inconclusive results and prevent unnecessary diagnostic surgery. However, the effectiveness of CNB in patients with suspicious thyroid nodules has not been fully evaluated. This prospective study aimed to determine the potential of CNB to assess thyroid nodules with suspicious ultrasound (US) features. Materials and Methods: Patients undergoing CNB for thyroid nodules with suspicious features on US were enrolled between May and August 2016. Diagnostic performance and the incidence of non-diagnostic results, inconclusive results, conclusive results, malignancy, unnecessary surgery, and complications were analyzed. Subgroup analysis according to nodule size was performed. The risk factors associated with inconclusive results were evaluated using multivariate logistic regression analysis. Results: A total of 93 patients (102 thyroid nodules) were evaluated. All samples obtained from CNB were adequate for diagnosis. Inconclusive results were seen in 12.7% of cases. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value for diagnosis of malignancy were 93.8%, 100%, 100%, 78.9%, and 95%, respectively. None of the patients underwent unnecessary surgery. The diagnostic performance was not significantly different according to nodule size. On multivariate logistic regression analysis, larger nodule size and shorter needle length were independent risk factors associated with inconclusive results. Conclusion: Samples obtained by CNB were sufficient for diagnosis in all cases and resulted in high diagnostic values and conclusive results in the evaluation of suspicious thyroid nodules. These findings indicated that CNB is a promising diagnostic tool for suspicious thyroid nodules.

From Machine Learning Algorithms to Superior Customer Experience: Business Implications of Machine Learning-Driven Data Analytics in the Hospitality Industry

  • Egor Cherenkov;Vlad Benga;Minwoo Lee;Neil Nandwani;Kenan Raguin;Marie Clementine Sueur;Guohao Sun
    • Journal of Smart Tourism
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    • 제4권2호
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    • pp.5-14
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    • 2024
  • This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

CCNA1 Promoter Methylation: a Potential Marker for Grading Papanicolaou Smear Cervical Squamous Intraepithelial Lesions

  • Chujan, Suthipong;Kitkumthorn, Nakarin;Siriangkul, Sumalee;Mutirangura, Apiwat
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권18호
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    • pp.7971-7975
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    • 2014
  • Background: From our previous study, we established that cyclin A1 (CCNA1) promoter methylation is strongly correlated with multistep progression of HPV-associated cervical cancer, suggesting potential use as a diagnostic maker of disease. Objectives: The purpose of the present study was to assess the prevalence of CCNA1 promoter methylation in residual cervical cells isolated from liquid-based cytology that underwent hrHPV DNA screening for cervical cancer, and then to evaluate this marker for diagnostic accuracy using parameters like sensitivity, specificity, predictive values and likelihood ratio. Methods: In this retrospective study, histopathology was used as the gold standard method with specimens separated into the following groups: negative (n=31), low-grade squamous intraepithelial lesions (LSIL, n=34) and high-grade squamous intraepithelial lesions or worse (HSIL+, n=32). The hrHPV was detected by Hybrid Capture 2 (HC2) and CCNA1 promoter methylation was examined by CCNA1 duplex methylation specific PCR. Results: The results showed the frequencies of CCNA1 promoter methylation were 0%, 5.88% and 83.33%, while the percentages of hrHPV were 66.67%, 82.35% and 100% in the negative, LSIL and HSIL+ groups, respectively. Although hrHPV infection showed high frequency in all three groups, it could not differentiate between the different groups and grades of precancerous lesions. In contrast, CCNA1 promoter methylation clearly distinguished between negative/LSIL and HSIL+, with high levels of all statistic parameters. Conclusion: CCNA1 promoter methylation is a potential marker for distinguishing between histologic negative/LSIL and HSIL+using cervical cytology samples.

Should TPP Be Formed? On the Potential Economic, Governance, and Conflict-Reducing Impacts of the Trans-Pacific Partnership Agreement

  • Bergstrand, Jeffrey H.
    • East Asian Economic Review
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    • 제20권3호
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    • pp.279-309
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    • 2016
  • The proposed Trans-Pacific Partnership (TPP) is a free trade agreement among 12 Pacific Rim countries whose joint gross domestic products (GDPs) account for 36 percent of world GDP and whose mutual trade accounts for approximately 24 percent of world trade. As for most proposed free trade agreements (FTAs), trade economists have provided ex ante computable general equilibrium (CGE) estimates to predict the trade, employment, and real per capita income effects of this agreement, such as ITC (2016). This paper-intended to complement these studies-examines the potential impacts of TPP beyond such traditional CGE estimates, taking a broader economic, governance, and historical perspective. First, we contrast these traditional CGE trade and welfare estimates that treat all firms within an industry as homogeneous with more recent CGE analyses that allow firms' productivities to be heterogeneous. We show that the latter models' trade predictions are much more consistent with ex post empirical evidence of average trade effects of FTAs. Second, empirical evidence now strongly confirms the existence of FTA "contagion." We review this evidence and show that predictive models of the evolution of FTAs indicate that the TPP should be formed. With China now having formed 12 FTAs and negotiating five new ones (including a sixteen member Asia-Pacific FTA), the United States would likely face considerable trade diversion without the TPP. Third, we examine empirical evidence on the likely further economic growth implications of FTAs by reducing firms' uncertainty over trade relations and trade policies. Fourth, we examine empirical evidence on the additional impact of FTAs on consolidating democratic institutions in countries. The TPP would likely help consolidate some of the less mature democracies. Fifth, we examine empirical evidence on the reductions of conflicts (and enhanced peace) between countries owing to the formations of FTAs. We conclude the paper noting that the potential net benefits to member countries of the proposed TPP extend well beyond the real income gains to households based upon traditional CGE models.

Evaluation of Eye Irritation Potential of Solid Substance with New 3D Reconstructed Human Cornea Model, MCTT HCETM

  • Jang, Won-hee;Jung, Kyoung-mi;Yang, Hye-ri;Lee, Miri;Jung, Haeng-Sun;Lee, Su-Hyon;Park, Miyoung;Lim, Kyung-Min
    • Biomolecules & Therapeutics
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    • 제23권4호
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    • pp.379-385
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    • 2015
  • The eye irritation potential of drug candidates or pharmaceutical ingredients should be evaluated if there is a possibility of ocular exposure. Traditionally, the ocular irritation has been evaluated by the rabbit Draize test. However, rabbit eyes are more sensitive to irritants than human eyes, therefore substantial level of false positives are unavoidable. To resolve this species difference, several three-dimensional human corneal epithelial (HCE) models have been developed as alternative eye irritation test methods. Recently, we introduced a new HCE model, MCTT HCE$^{TM}$ which is reconstructed with non-transformed human corneal cells from limbal tissues. Here, we examined if MCTT HCE$^{TM}$ can be employed to evaluate eye irritation potential of solid substances. Through optimization of washing method and exposure time, treatment time was established as 10 min and washing procedure was set up as 4 times of washing with 10 mL of PBS and shaking in 30 mL of PBS in a beaker. With the established eye irritation test protocol, 11 solid substances (5 non-irritants, 6 irritants) were evaluated which demonstrated an excellent predictive capacity (100% accuracy, 100% specificity and 100% sensitivity). We also compared the performance of our test method with rabbit Draize test results and in vitro cytotoxicity test with 2D human corneal epithelial cell lines.

BASS 확산 모형을 이용한 국내 자동차 외장 램프 LED 수요예측 분석 (Domestic Automotive Exterior Lamp-LEDs Demand and Forecasting using BASS Diffusion Model)

  • 이재흔
    • 품질경영학회지
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    • 제50권3호
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    • pp.349-371
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    • 2022
  • Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

Prognostic Value of an Immune Long Non-Coding RNA Signature in Liver Hepatocellular Carcinoma

  • Rui Kong;Nan Wang;Chun li Zhou;Jie Lu
    • Journal of Microbiology and Biotechnology
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    • 제34권4호
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    • pp.958-968
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    • 2024
  • In recent years, there has been a growing recognition of the important role that long non-coding RNAs (lncRNAs) play in the immunological process of hepatocellular carcinoma (LIHC). An increasing number of studies have shown that certain lncRNAs hold great potential as viable options for diagnosis and treatment in clinical practice. The primary objective of our investigation was to devise an immune lncRNA profile to explore the significance of immune-associated lncRNAs in the accurate diagnosis and prognosis of LIHC. Gene expression profiles of LIHC samples obtained from TCGA database were screened for immune-related genes. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate Cox analysis. Then, the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were performed to evaluate the capability of the immune lncRNA signature as a prognostic indicator. Six long non-coding RNAs were identified via correlation analysis and Cox regression analysis considering their interactions with immune genes. Subsequently, tumor samples were categorized into two distinct risk groups based on different clinical outcomes. Stratification analysis indicated that the prognostic ability of this signature acted as an independent factor. The Kaplan-Meier method was employed to conduct survival analysis, results showed a significant difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Additionally, data obtained from gene set enrichment analysis (GSEA) revealed several potential biological processes in which these biomarkers may be involved. To summarize, this study demonstrated that this six-lncRNA signature could be identified as a potential factor that can independently predict the prognosis of LIHC patients.

한반도에서 기후변화에 따른 수변 외래식물인 털물참새피의 분포 변화 예측 (Prediction of Changes in the Potential Distribution of a Waterfront Alien Plant, Paspalum distichum var. indutum, under Climate Change in the Korean Peninsula)

  • 조강현;이승현
    • Ecology and Resilient Infrastructure
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    • 제2권3호
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    • pp.206-215
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    • 2015
  • 기후변화에 따른 침입외래식물의 잠재적 분포지를 예측하는 것은 하천과 저수지에서 생물다양성 보전과 생태적 관리를 위하여 중요하고 해결해야 할 과제이다. 본 연구에서는 한반도에서 털물참새피 (Paspalum distichum var. indutum)의 잠재적 미래 분포에 미치는 기후변화의 영향을 파악하였다. 털물참새피는 담수생태계의 수변에서 심각한 경제적, 환경적 영향을 미치는 침입 초본식물이다. 현재와 미래의 기후에서 털물참새피의 잠재적 분포를 추정하기 위하여 Maxent 모델을 적용하였다. 기후변화의 영향을 파악하기 위하여 현재 기후 자료로서 Worldclim 1.4의 19개 기후 변수를 사용하였고, 미래의 기후 자료로서 RCP 2.6와 RCP 8.5 시나리오에 따라서 HadGEM2- AO에 의하여 예측된 기후 변수를 사용하였다. 예측된 털물참새피의 현재 잠재분포지는 실제 위치 자료와 거의 일치하였다. 이 식물의 잠재 분포에 영향을 미치는 환경 변수는 가장 따뜻한 분기의 강수량, 연평균기온 및 가장 추운 분기의 평균기온이었다. 2050년에 기후변화에 따른 털물참새피의 분포 예측에 의하면 이 식물의 현재 분포지에서는 기후 적합성이 대체로 감소하였고, 이 식물이 보다 내륙과 북쪽으로 분포지가 확대되었다. 본 연구에서 사용한 예측 모델은 잠재적 분포를 이해하고 분포 변화에 미치는 기후변화의 영향을 파악하며 외래식물에 의한 생물적 침입의 위해성을 효과적으로 관리하는데 유용할 것으로 기대된다.

Does Immunohistochemistry Provide Additional Prognostic Data in Gastrointestinal Stromal Tumors?

  • Demir, Lutfiye;Ekinci, Nese;Erten, Cigdem;Kucukzeybek, Yuksel;Alacacioglu, Ahmet;Somali, Isil;Can, Alper;Dirican, Ahmet;Bayoglu, Vedat;Akyol, Murat;Cakalagaoglu, Fulya;Tarhan, Mustafa Oktay
    • Asian Pacific Journal of Cancer Prevention
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    • 제14권8호
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    • pp.4751-4758
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    • 2013
  • Background: To investigate the predictive and prognostic effects of clinicopathologic and immunohistochemical (IHC) features in patients with gastrointestinal stromal tumours (GISTs). Materials and Methods: Fifty-six patients who were diagnosed with GIST between 2002 and 2012 were retrospectively evaluated. Relationships between clinicopathologic/immunohistochemical factors and prognosis were investigated. Results: Median overall survival (OS) of the whole study group was 74.9 months (42.8-107.1 months), while it was 95.2 months in resectable and 44.7 months in metastatic patients respectively (p=0.007). Epitheliolid tumor morphology was significantly associated with shortened OS as compared to other histologies (p=0.001). SMA(+) tumours were significantly correlated with low (<10/50HPF) mitotic activity (p=0.034). Moreover, SMA(+) patients tended to survive longer and had significantly longer disease-free survival (DFS) times than SMA (-) patients (37.7 months vs 15.9 months; p=0.002). High Ki-67 level (${\geq}30%$) was significantly associated with shorter OS (34 vs 95.2 months; 95%CI; p=0.001). CD34 (-) tumours were significantly associated with low proliferative tumours (Ki-67<%10) (p=0.026). Median PFS (progression-free survival) of the patients who received imatinib was 36 months (27.7-44.2 months). CD34 (-) patients had significantly longer PFS times than that of negative tumours; (50.8 vs 29.8 months; p=0.045). S100 and desmin expression did not play any role in predicting the prognosis of GISTs. Multivariate analysis demonstrated that ${\geq}10/50HPF$ mitotic activity/HPF was the only independent factor for risk of death in GIST patients. Conclusions: Despite the negative prognostic and predictive effect of high Ki-67 and CD34 expression, mitotic activity remains the strongest prognostic factor in GIST patients. SMA positivity seems to affect GIST prognosis positively. However, large-scale, multicenter studies are required to provide supportive data for these findings.

온도와 시간을 주요 변수로 한 냉장 돈육에서의 native isolated Listeria monocytogenes에 대한 성장예측모델 (Predictive Growth Model of Native Isolated Listeria monocytogenes on raw pork as a Function of Temperature and Time)

  • 홍종해;심우창;천석조;김용수;오덕환;하상도;최원상;박경진
    • 한국식품과학회지
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    • 제37권5호
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    • pp.850-855
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    • 2005
  • 본 연구는 냉장돈육에서의 식중독 원인균이면서 냉장온도에서 성장이 가능한 병원성균인 L. monocytogenes에 대한 적절한 위생관리를 제시하기 위하여 포장돈육 작업장 원료돈육에서 분리된 야생균주 L. monocytogenes 이용하여 돈육포장공정 및 유통조건에서의 L. mnocytogenes에 대한 성장예측모델을 제시하고자 실시하였다. 성장실험은 온도 5, 10, 15, $20^{\circ}C$ 시간은 0, 1, 2, 3, 18, 48, 120시간에서 실시하였으며, 이를 바탕으로 온도별 Gompertz value인 A, C, B, M의 값과 Growth kinetic인 exponential growth rate(EGR), generation time(GT), lag phase duration(LPD), maximum population density(MPD)를 산출하였다. GT, LPD는 온도가 상승할수록 그 값이 점점 낮아지는 경향을 나타났으며, EGR의 경우는 반대로 온도가 높아질수록 점점 높아지는 경향을 나타냈다. Gompertz value중 B와 M 값을 이용하여 온도를 주요 control factor로 선정한 반응표면분석(Response surface analysis)을 실시하여 온도에 따른 다항식을 산출하였고 이 식을 Gompertz 식에 적용하여 온도와 시간에 따른 냉장돈육에서의 L. monocytogenes에 대한 성장정도를 예측할 수 있는 성장예측모델을 제시하였다. 개발된 성장예측모델에 대한 검증은 GT, LPD, EGR에 대한 실험값과 예측값의 비교를 통하여 실시하였으며, 그 결과 GT, LPD, EGR 모두 통계적으로 유의하게 나타났다(p<0.01). 따라서 이 모델은 risk assessment 중 exposure assessment를 위한 성장예측모델로 충분히 이용가능 한 것으로 보이며, 추후 냉장돈육 위성관리기준에 대한 과학적 근거자료로 활용될 수 있을 것으로 보인다.