ROC Methods Research Articles

Identifying the mitochondrial ribosomal protein MRPL13 as an oncogenic RBP that promotes proliferation, migration, and anti-apoptotic effects in esophageal cancer cells

PurposeThe correct transcription, processing and function of RNAs are the prerequisites of cell life. RNA-binding proteins (RBPs) are responsible for coordinating the biogenesis of RNA in cells and play a central role in the cellular processes of many diseases. Esophageal cancer (ESCA) is a high incidence of human malignant tumor with a complex molecular mechanism. The purpose of this study was to investigate the important role of RBPs in ESCA. MethodsTCGA-ESCA, IMvigor-210 and GSE53624 repositories were used to obtain esophageal cancer omics data and clinical information. Differential expression analysis, protein-protein interaction and LASSO methods were used to construct the risk signature. Kaplan-Meier and ROC methods were used to analyze the relationship between risk and prognostic. XCell, QUANRISEQ, MCPcounter, EPIC, CIBERSORT, ssGSEA and Estimate algorithm were used to evaluate the abundance of various components of the immune microenvironment. Gene enrichment variation analysis (GSVA) was performed to analyze molecular differences. EdU, transwell and flow cytometry assays were performed to detected proliferation, migration and apoptosis level of ESCA cell lines. ResultsWe visualized the core internal protein-protein interaction of 279 differential expression RBPs, and a 7-RBP risk signature was established. Riskscore was negative correlated with survival time. Meanwhile, high risk groups portend advanced stage, more macrophage and less CD4+ T/master cell infiltration enriched, hyperactive proliferation signal, and different therapeutic response. Finally, we found that RBP MRPL13 is upregulated in esophageal cancer, and its expression is associated with patients’ prognostic. MRPL13 is closely correlated with multiple signaling pathways, as well MRPL13 could promote cell proliferation, migration and anti-apoptosis. ConclusionRNA binding proteins are prognostic marker of esophageal cancer, which could provide clinical diagnosis and treatment strategies. RBP MRPL13 facilitated esophageal cancer progression.

Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and invitro experiments.

The aetiology of bone metastasis in prostate cancer (PCa) remains unclear. This study aims to identify hub genes involved in this process. We utilized machine learning, GO, KEGG, GSEA, Single-cell analysis, ROC methods to identify hub genes for bone metastasis in PCa using the TCGA and GEO databases. Potential drugs targeting these genes were identified. We validated these results using 16 specimens from patients with PCa and analysed the relationship between the hub genes and clinical features. The impact of APOC1 on PCa was assessed through invitro experiments. Seven hub genes with AUC values of 0.727-0.926 were identified. APOC1, CFH, NUSAP1 and LGALS1 were highly expressed in bone metastasis tissues, while NR4A2, ADRB2 and ZNF331 exhibited an opposite trend. Immunohistochemistry further confirmed these results. The oxidative phosphorylation pathway was significantly enriched by the identified genes. Aflatoxin B1, benzo(a)pyrene, cyclosporine were identified as potential drugs. APOC1 expression was correlated with clinical features of PCa metastasis. Silencing APOC1 significantly inhibited PCa cell proliferation, clonality, and migration invitro. This study identified 7 hub genes that potentially facilitate bone metastasis in PCa through mitochondrial metabolic reprogramming. APOC1 emerged as a promising therapeutic target and prognostic marker for PCa with bone metastasis.

Implementation of the ROC and CPI Methods for New Employee Selection at PT. Neora Infrastructure Indonesia

Implementation of the ROC and CPI Methods for New Employee Selection at PT. Neora Infrastructure Indonesia

IL-6 significantly correlated with the prognosis in low-grade glioma and the mediating effect of immune microenvironment.

To screen immune-related prognostic biomarkers in low-grade glioma (LGG), and reveal the potential regulatory mechanism. The differential expressed genes (DEGs) between alive and dead patients were initially identified, then the key common genes between DEGs and immune-related genes were obtained. Regarding the key DEGs associated with the overall survival (OS), their clinical value was assessed by Kaplan-Meier, RCS, logistic regression, ROC, and decision curve analysis methods. We also assessed the role of immune infiltration on the association between key DEGs and OS. All the analyses were based on the TGCA-LGG data. Finally, we conducted the molecular docking analysis to explore the targeting binding of key DEGs with the therapeutic agents in LGG. Among 146 DEGs, only interleukin-6 (IL-6) was finally screened as an immune-related biomarker. High expression of IL-6 significantly correlated with poor OS time (all P < .05), showing a linear relationship. The combination of IL-6 with IDH1 mutation had the most favorable prediction performance on survival status and they achieved a good clinical net benefit. Next, we found a significant relationship between IL-6 and immune microenvironment score, and the immune microenvironment played a mediating effect on the association of IL-6 with survival (all P < .05). Detailly, IL-6 was positively related to M1 macrophage infiltration abundance and its biomarkers (all P < .05). Finally, we obtained 4 therapeutic agents in LGG targeting IL-6, and their targeting binding relationships were all verified. IL6, as an immune-related biomarker, was associated with the prognosis in LGG, and it can be a therapeutic target in LGG.

Combination of ROC and MFEP Methods in Providing Credit to the Mislina Cooperative

One of the activities of the cooperative is to offer loans to customers and make loans based on several requirements that must be met by applicants who wish to borrow. So far, in determining the provision of cooperative loans to mislina cooperatives, it is considered that they are not careful and selective in providing loans which has an impact on increasing the ratio of loans in arrears. The process of granting loans to mislina cooperatives is still done manually and without doing calculations with special calculation methods that can help do rankings. The research objective was to apply the ROC and MFEP combination methods in designing a decision support system for mislina cooperative loan assessments. The method used is a decision support system using a combination of ROC and MFEP methods. Based on the results of implementing a combination of ROC and MFEP, the results of the system being built can make it easier to determine the provision of pimjama loans to Mislina cooperatives so that they are more effective and efficient. The results of the ROC and MFEP combination tests resulted in a decision that the highest alternative was sayem with a final total value of 2.85.

Implementasi Metode Operational Competitiveness Rating Analysis (OCRA) Dengan Pembobotan Rank Order Centroid (ROC) Dalam Pengambilan Keputusan Penilaian Supir Barang Terbaik

An assessment of a position is very important for a company in order to improve good performance. One of them is a goods driver, some of the duties of a goods driver at CV.Solusi are to maintain the safety and condition of the goods to be sent. The assessment of the best goods drivers is a form of assessment of the quality and quantity produced by the drivers. The problem faced by CV.Solution in assessing the best goods drivers is the lack of transparency and only relying on the memory of the party making the decision. Based on the problems that have been described, the process of assessing the best goods driver requires a Decision Support System (DSS) which can assist in making more effective decisions regarding the assessment of the best goods driver. Building a SPK using the OCRA method and ROC weighting in creating a system can make it easier for users to do this. The results of this research show that there is a Decision Support System (DSS) with the implementation of the OCRA and ROC methods, the assessment carried out by CV.Solusi produces focused and directed decisions so that the decision results are effective and efficient.

Cutoff estimation and construction of their confidence intervals for continuous biomarkers under ternary umbrella and tree stochastic ordering settings.

Tuberculosis (TB) studies often involve four different states under consideration, namely, "healthy," "latent infection," "pulmonary active disease," and "extra-pulmonary active disease." While highly accurate clinical diagnosis tests do exist, they are expensive and generally not accessible in regions where they are most needed; thus, there is an interest in assessing the accuracy of new and easily obtainable biomarkers. For some such biomarkers, the typical stochastic ordering assumption might not be justified for all disease classes under study, and usual ROC methodologies that involve ROC surfaces and hypersurfaces are inadequate. Different types of orderings may be appropriate depending on the setting, and these may involve a number of ambiguously ordered groups that stochastically exhibit larger (or lower) marker scores than the remaining groups. Recently, there has been scientific interest on ROC methods that can accommodate these so-called "tree" or "umbrella" orderings. However, there is limited work discussing the estimation of cutoffs in such settings. In this article, we discuss the estimation and inference around optimized cutoffs when accounting for such configurations. We explore different cutoff alternatives and provide parametric, flexible parametric, and non-parametric kernel-based approaches for estimation and inference. We evaluate our approaches using simulations and illustrate them through a real data set that involves TB patients.

Decision Support System for Determining the Best Coffee Shop Applying the OCRA Method using ROC Weighting

The place of coffee sales, or more commonly known as a coffee shop, not only offers coffee but also serves a variety of hot and cold beverages. Many individuals, especially young people and students, choose to spend their time in modern coffee shops to sit and relax. Currently, coffee shops are often used as places for discussions, exchanging ideas, or simply relieving stress after activities. Coffee shops have become centers of social interaction with adequate service facilities. Although coffee shops are widespread, many people are not careful in choosing them. When choosing a coffee shop, it is important to select one that not only provides a comfortable environment but also serves the best-tasting coffee. The process of choosing the best coffee shop involves considerations such as price, taste quality, service, atmosphere, and cleanliness. To address this challenge, the author deems it essential to implement a Decision Support System (DSS). DSS is a field of science that utilizes technology to assist in problem-solving and accurate decision-making, without being manipulable. In the context of this research, the author uses the OCRA and ROC methods, as both are known as objective and easily understood methods. By applying the OCRA and ROC methods, the research results show that Gen’s Semar Cafe, with a score of 1.594, is selected as the best coffee shop.

Decision Support System for Student Exchange Selection in Support of Independent Campus using the MAUT and ROC Methods

Independent campus is an off-campus learning activity as an opportunity for students to hone skills in preparation for entering the world of work. One of the programs held is the exchange of students to be able to study on campuses or companies that join the Ministry of Education and Culture, Research and Technology. With the current independent campus program, almost all universities open up opportunities for students to register. However, because there are too many students who register, the campus has difficulty in choosing some students who can be accepted according to the criteria set by the party. For this reason, a Decision Support System is needed that applies the MAUT method along with the use of ROC to produce the best preference value. The calculation of several data samples resulted in the best final utility value in the selection of independent campus student exchanges in Alternative A2 with the best final utility value of 0.9700

Penerapan Metode Additive Ratio Assessment (ARAS) dan Ranking of Centroid (ROC) dalam Pemilihan Layanan Akomodasi dan Local Cuisine

Salatiga is a gastronomic city with various types of traditional food and drinks and is a recreational tourism city with exciting and crowded mountain natural scenery. The availability of accommodation services and local cuisine adds to visitors' preferences to enjoy local culinary dishes. This study offers an initiative to use the Additive Ratio Assessment (ARAS) method in selecting the best accommodation and restaurant services in Salatiga based on Tripadvisor data. The stages in the calculation process based on the ARAS method are as follows: the stage of determining the value of criteria, weights, alternatives, and optimal values; the stage of converting the value of the criterion into a decision matrix; the stage of normalization of the decision matrix for all criteria; stage of calculating the value of utility; Ranking stage. The calculation results show that in the context of accommodation services, A5 occupies the first position with a Ki value of 0.887, A4 occupies the second position with a Ki value of 0.870, and A1 occupies the third position with a Ki value of 0.849. Meanwhile, in the context of local cuisine, A2 occupies the first position with a Ki value of 0.951, A5 occupies the second position with a Ki value of 0.914, and A4 occupies the third position with a Ki value of 0.854. This shows that ARAS and ROC methods can produce the best recommendations for tourists who want to use accommodation services and enjoy local cuisine in Salatiga City.

Sistem Pendukung Keputusan Rekomendasi Wedding Organizer Terbaik Menerapkan Metode MOORA dan Pembobotan ROC

Wedding Organizer provides a variety of services to help couples prepare and organize their wedding according to their wishes. However, with so many choices of wedding planners in Medan, couples often have difficulty choosing the best one for their needs. Decision Support System (DSS) is a strategy that assists in decision making by applying mathematical and statistical techniques to available data. In the case of selecting a Wedding Organizer, SPK can be used to assist couples in assessing and choosing the optimal option that matches the parameters that have been set. This complex selection process involves careful consideration of price, quality of service, reputation, portfolio and experience. The MOORA method with the ROC weighting method is one of the methods that can be used in DSS to select the best alternative based on several criteria. The MOORA method allows ranking alternatives based on different criteria, while the ROC method weighting can help overcome data imbalance problems and optimize model performance in decision making. From the results of calculations using the MOORA and ROC methods that have been carried out from 8 alternatives, it produces recommendations for the wedding organizer, namely getting 4 highly recommended alternatives while 4 other alternatives are sufficiently recommended. The research findings show that the application of the MOORA method with the ROC Method assessment is able to provide recommendations that are more precise and in accordance with the established criteria, assisting couples in making accurate and efficient decisions when choosing the Wedding Organizer that best suits their wishes and needs.

Sistem Pendukung Keputusan Pemilihan Staf Karyawan Bpn Terbaik Di Wilayah Kota Medan Dengan Mengunakan Metode Moora Dengan Pembobotan Roc

Decision Support System (DSS) is a decision support system that can help in handling or solving problems in a company or in the daily environment, in determining a problem we need data that we will take in a company or in the environment. In writing this is an example of a problem that is currently happening with the case study of the Selection of the Best BPN Employees in the City of Medan, therefore the author uses a method that will be able to find the best employee data, therefore the author creates a decision support system that will be able to determine the best BPN employee assessment process in the city of Medan. Where this system is a system that has a very important role in decision making. The system is DSS, where DSS is one of the systems that can assist in solving each problem by requiring data and methods contained in the DSS in order to obtain more relevant information and support in making each decision. In completing this research, the writer has to find the weight value of the criterion data where the writer uses the ROC method to produce the weight value and after that the writer also searches for the ranking value using the MOORA method. And where to produce ranking values in the MOORA method, the author must work according to predetermined steps in order to obtain precise and accurate reference values. The ROC and MOORA methods really help writers in generating values accurately.This decision support system was made using the MOORA method with ROC weighting where this method can be used or can be used as a reference in determining a problem because it aims to find out how many employees are Top Talent (Best Employee), after testing it is given a weight value on criteria and can be modified which aims to find out how many criteria will be added in each criterion which has its own weight value and after that a ranking is made in which the ranking can already determine the best BPN employee in the city of Medan, namely (T3) Anggi Alfarissi HSB with a score of 1,157. So because of this it was confirmed or very easy for the team to select in decision-making and were selected as the best BPN employees in the city of Medan.

Responsiveness and Minimal Important Change of the Arabic Disabilities of the Arm, Shoulder and Hand (DASH) in Patients with Upper Extremity Musculoskeletal Disorders.

The aim of this study was to examine the responsiveness of the Arabic Disabilities of the Arm, Shoulder and Hand (DASH) and to quantify its minimal important change (MIC) for improvement. People with upper extremity musculoskeletal problems who were receiving physical therapy were evaluated at baseline and again during a follow-up appointment, with a median time frame of 7 days between the two testing sessions (range of 6 to 72 days). The participants completed the Arabic DASH, Global Assessment of Function (GAF), Numeric Pain Rating Scale (NPRS) and Global Rating of Change Scale (GRC). The responsiveness of the Arabic DASH was assessed by examining the pre-specified hypotheses. The MIC for improvement was determined using the receiver operating characteristic method (MICROC) and the predictive modeling method (MICpred). As hypothesized, a change in the Arabic DASH demonstrated a significant positive correlation with changes in the GAF (r = 0.69), NPRS (r = 0.68) and GRC (r = 0.73). Consistent with our hypotheses, the DASH change scores could be used to differentiate between participants who improved and those who did not improve (area under the receiver operating characteristic curve = 0.87), and they showed a large magnitude of change (effect size = 1.53, standardized response mean = 1.42) in patients who improved. All the hypotheses specified a priori were supported by the results. The Arabic DASH MICROC and MICpred were estimated to be 14.22 and 14.85. The interaction between the DASH change and baseline score was not a significant predictor of status (improved vs. not improved) (p = 0.75), indicating that the DASH MIC was not baseline-dependent. The Arabic DASH demonstrated sufficient responsiveness, supporting the idea that the Arabic DASH is capable of detecting changes in upper extremity function over time. The value of the Arabic DASH MIC was similar when estimated using the predictive modeling and ROC methods, and the MIC was not dependent on baseline status.

Sistem Pendukung Keputusan Menentukan Aplikasi Chat Terbaik Menggunakan Metode OCRA Dengan Pembobotan ROC

In this study, a study was conducted to determine the Best Chat Application, the more we enter the digital era, the more applications and communication media or sending messages that appear. So researchers want to do research to determine which chat application is the best that people can use and unfortunately it is suitable for use today, then a system is applied that can help to decide, namely a Decision Support System (DSS) which can simplify the process of selecting the Best Chat Application by implementing 5 criteria i.e. Security, Number of Downloads, Reviews, Features, Storage. So we need a system that can make decisions by using SPK that applies the ROC and Operational Comprtitiveness Rating Analysis(OCRA) methods in getting the weighting value for each criterion and preference value from the best alternative, namely alternative A¬1 with the name Whatsapp Application with a preference value of 128,3123

Penerapan Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Dalam Pemilihan Kepala Laboratorium Menggunakan Pembobotan Rank Order Centroid (ROC)

In selecting the head of the laboratory, someone who has extensive knowledge in the specific field of the laboratory is needed, as well as good management and leadership skills. They may also be involved in developing new methods, selecting equipment, and developing laboratory policies. However, the challenge in the selection process for a new laboratory head is the high number of applicants and a series of selection stages which are time-consuming, including administrative selection, competency evaluation, and interviews. This causes difficulties for schools in making decisions to get candidates for laboratory heads that match their expectations. In solving problems in laboratory selection, the authors make 5 criteria including qualifications, experience, leadership, communication skills, and responsibility. So this research also needs a system that can help to solve existing problems. A system that can help solve problems is a Decision Support System (SPK). In completing this research, the writer has to find the weight value of the criterion data where the writer uses the ROC method to produce the weight value and after that the writer also searches for the ranking value using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The produce of ranking values in the TOPSIS method, the author must work according to predetermined steps in order to obtain precise and accurate preference values. The ROC and TOPSIS methods really help the writer in generating values accurately. So from the above calculations using the TOPSIS method the chosen head of the laboratory is Zakiyah Alifah with a total value of 1.

Sistem Pendukung Keputusan Penerapan Metode OCRA dalam Seleksi Penerima Bantuan Penduduk Miskin dengan Pembobotan ROC

The research conducted was the selection of recipients of assistance to the poor in Perk Village. Old Country in the district. District Downstream Labuhan Batu, namely BLT-DD or Village Fund Direct Cash Assistance. The process of distributing aid to the poor is still done conventionally in the selection of recipients of assistance to the poor, so the process of distributing funds is very long. This study applies a Decision Support System (SPK) which is used as a system that can facilitate the selection process for recipients of assistance to the poor. In the selection process for recipients of assistance, the poor must meet 5 criteria, namely Chronic Disease, Income, Occupation, Number of Dependents, and House Status. Thus, a system that can make decisions is needed, namely SPK by applying the ROC and OCRA methods to get the weight value of each criterion and the preference value of the best alternative, namely alternative A4 on behalf of Suadi with a preference value of 1.3757

Decision Support System for Extreme Poverty BLT Recipients Combining the ROC and WASPAS Methods

The Covid-19 pandemic has begun to be under control and the basis for the Village Fund BLT distribution has been adjusted. BLT Dana Desa aims to increase the income of extremely poor families in the village. In determining and determining prospective Beneficiary Families (KPM), each village will be guided by the data for the Acceleration of Extreme Poverty Elimination (PPKE) provided by the central government through the local government which will later be verified by the village government. Therefore, a Decision Support System is needed to find out who really deserves assistance, so that the allocation can be right on target according to predetermined criteria. In this study the results of this study show that the proposed model can be used well in conducting the selection process for laboratory assistant admissions. In this research, the use of ROC is able to provide appropriate criteria weights based on the level of importance of the criteria from the decision maker. Meanwhile, the use of the WASPAS method is able to produce decisions in the form of the best alternatives that can be used to help decision makers. From the calculation process that has been done, it can be concluded that Sunardi got the highest score, namely 0.7276 and Muksin got the lowest score, namely 0.5491. The existence of this system can make it easier for the government, especially villages, to identify beneficiaries and minimize errors in selecting beneficiaries.

Combination of ROC and MFEP Methods on the Acceptance of Rainwater Gutter Installer

The services of building construction companies in today's modern era are increasingly in demand by the wider community to get the best building results. Installing a rainwater tap in a building is one of the most important parts to pay attention to so that consumers are not disappointed. Therefore, the head of a building construction company that offers services in this field must be careful in the process of accepting rainwater gutter installer. The criteria used to acceptance of rainwater gutter installerin this study consisted of insight, work experience, health, and age criteria. Data collection techniques used in this study were literature studies and field studies. In this study the authors apply the ROC and MFEP methods to obtain the decision making of acceptance of rainwater gutter installer. In the results of this study an alternative named Rudiasyah (0.427111) has the highest value compared to other alternatives. So in this study Rudiasyah became the most recommended alternative to be accepted as a rainwater gutter installer

A cuproptosis random forest cox score model-based evaluation of prognosis, mutation characterization, immune infiltration, and drug sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma is the third most deadly malignant tumor in the world with a poor prognosis. Although immunotherapy represents a promising therapeutic approach for HCC, the overall response rate of HCC patients to immunotherapy is less than 30%. Therefore, it is of great significance to explore prognostic factors and investigate the associated tumor immune microenvironment features. By analyzing RNA-seq data of the TCGA-LIHC cohort, the set of cuproptosis related genes was extracted via correlation analysis as a generalization feature. Then, a random forest cox prognostic model was constructed and the cuproptosis random forest cox score was built by random forest feature filtering and univariate multivariate cox regression analysis. Subsequently, the prognosis prediction of CRFCS was evaluated via analyzing data of independent cohorts from GEO and ICGC by using KM and ROC methods. Moreover, mutation characterization, immune cell infiltration, immune evasion, and drug sensitivity of CRFCS in HCC were assessed. A cuproptosis random forest cox score was built based on a generalization feature of four cuproptosis related genes. Patients in the high CRFCS group exhibited a lower overall survival. Univariate multivariate Cox regression analysis validated CRFCS as an independent prognostic indicator. ROC analysis revealed that CRFCS was a good predictor of HCC (AUC =0.82). Mutation analysis manifested that microsatellite instability (MSI) was significantly increased in the high CRFCS group. Meanwhile, tumor microenvironment analysis showed that the high CRFCS group displayed much more immune cell infiltration compared with the low CRFCS group. The immune escape assessment analysis demonstrated that the high CRFCS group displayed a decreased TIDE score indicating a lower immune escape probability in the high CRFCS group compared with the low CRFCS group. Interestingly, immune checkpoints were highly expressed in the high CRFCS group. Drug sensitivity analysis revealed that HCC patients from the high CRFCS group had a lower IC50 of sorafenib than that from the low CRFCS group. In this study, we constructed a cuproptosis random forest cox score (CRFCS) model. CRFCS was revealed to be a potential independent prognostic indicator of HCC and high CRFCS samples showed a poor prognosis. Interestingly, CRFCS were correlated with TME characteristics as well as clinical treatment efficacy. Importantly, compared with the low CRFCS group, the high CRFCS group may benefit from immunotherapy and sorafenib treatment.

Kombinasi Metode Multi-Attribute Utility Theory (MAUT) dan Rank Order Centroid (ROC) dalam Pemilihan Kegiatan Ekstrakulikuler

This study aims to select extracurricular activities using the MAUT method using ROC weighting, so that this helps in understanding the consequences of various choices and identifying alternatives that best suit the preferences and goals of decision makers. The results of the study using a combination of MAUT and ROC methods resulted in extracurricular activity recommendations obtained for Karate extracurricular activities with a value of 0.654 getting rank 1. 2nd place was obtained for Futsal extracurricular activities with a value of 0.362, 3rd place was obtained for Scouting extracurricular activities with a value of 0.327.