LIVIVO - Search results -

Search results

Result 1 - 10 of total 54

Search options

Article: Chronic Obstructive Pulmonary Disease: Novel Genes Detection with Penalized Logistic Regression.

Gohari, Kimiya / Kazemnejad, Anoshirvan / Mostafaei, Shayan / Saberi, Samaneh / Sheidaei, Ali

2023 Volume 25, Issue 3, Page(s) 203–211

Abstract: Objective: This study aimed to introduce novel techniques for identifying the genes associated with developing chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods.: Materials and methods: This ... ...

Abstract	Objective: This study aimed to introduce novel techniques for identifying the genes associated with developing chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods. Materials and methods: This is a secondary analysis of the data from an experimental study. We used penalized logistic regressions with three different types of penalties included least absolute shrinkage and selection operator (LASSO), minimax concave penalty (MCP), and smoothly clipped absolute deviation (SCAD). The models were trained using genome-wide expression profiling to define gene networks relevant to the COPD stages. A 10-fold cross-validation scheme was used to evaluate the performance of the methods. In addition, we validate our results by the external validity approach. We reported the sensitivity, specificity, and area under curve (AUC) of the models. Results: There were 21, 22, and 18 significantly associated genes for LASSO, SCAD, and MCP models, respectively. The most statistically conservative method (detecting less significant features) was MCP detected 18 genes that were all detected by the other two approaches. The most appropriate approach was a SCAD penalized logistic regression (AUC= 96.26, sensitivity= 94.2, specificity= 86.96). In this study, we have a common panel of 18 genes in all three models that show a significant positive and negative correlation with COPD, in which RNF130, STX6, PLCB1, CACNA1G, LARP4B, LOC100507634, SLC38A2, and STIM2 showed the odds ratio (OR) more than 1. However, there was a slight difference between penalized methods. Conclusion: Regularization solves the serious dimensionality problem in using this kind of regression. More exploration of how these genes affect the outcome and mechanism is possible more quickly in this manner. The regression-based approaches we present could apply to overcoming this issue.
Language	English
Publishing date	2023-03-07
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2647430-X
ISSN	2228-5814 ; 2228-5806
ISSN (online)	2228-5814
ISSN	2228-5806
DOI	10.22074/cellj.2022.557389.1048
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article ; Online: Chronic Obstructive Pulmonary Disease

Kimiya Gohari / Anoshirvan Kazemnejad / Shayan Mostafaei / Samaneh Saberi / Ali Sheidaei

Cell Journal, Vol 25, Iss 3, Pp 203-

Novel Genes Detection with Penalized Logistic Regression

2023 Volume 211

Abstract: Objective: This study aimed to introduce novel techniques for identifying the genes associated with developingchronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods.Materials and Methods: This is a ... ...

Abstract	Objective: This study aimed to introduce novel techniques for identifying the genes associated with developingchronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using regression methods.Materials and Methods: This is a secondary analysis of the data from an experimental study. We used penalizedlogistic regressions with three different types of penalties included least absolute shrinkage and selection operator(LASSO), minimax concave penalty (MCP), and smoothly clipped absolute deviation (SCAD). The models weretrained using genome-wide expression profiling to define gene networks relevant to the COPD stages. A 10-foldcross-validation scheme was used to evaluate the performance of the methods. In addition, we validate ourresults by the external validity approach. We reported the sensitivity, specificity, and area under curve (AUC) ofthe models.Results: There were 21, 22, and 18 significantly associated genes for LASSO, SCAD, and MCP models, respectively.The most statistically conservative method (detecting less significant features) was MCP detected 18 genes that wereall detected by the other two approaches. The most appropriate approach was a SCAD penalized logistic regression(AUC= 96.26, sensitivity= 94.2, specificity= 86.96). In this study, we have a common panel of 18 genes in all threemodels that show a significant positive and negative correlation with COPD, in which RNF130, STX6, PLCB1,CACNA1G, LARP4B, LOC100507634, SLC38A2, and STIM2 showed the odds ratio (OR) more than 1. However, therewas a slight difference between penalized methods.Conclusion: Regularization solves the serious dimensionality problem in using this kind of regression. More explorationof how these genes affect the outcome and mechanism is possible more quickly in this manner. The regression-basedapproaches we present could apply to overcoming this issue.
Keywords	copd ; gene expression ; lasso ; mcp ; panelized logistic regression ; Medicine ; R ; Science ; Q
Subject code	519
Language	English
Publishing date	2023-03-01T00:00:00Z
Publisher	Royan Institute (ACECR), Tehran
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Clustering of countries according to the COVID-19 incidence and mortality rates.

Gohari, Kimiya / Kazemnejad, Anoshirvan / Sheidaei, Ali / Hajari, Sarah

BMC public health

2022 Volume 22, Issue 1, Page(s) 632

Abstract: Background: Two years after the beginning of the COVID-19 pandemic on December 29, 2021, there have been 281,808,270 confirmed cases of COVID-19, including 5,411,759 deaths. This information belongs to almost 216 Countries, areas, or territories facing ... ...

Abstract	Background: Two years after the beginning of the COVID-19 pandemic on December 29, 2021, there have been 281,808,270 confirmed cases of COVID-19, including 5,411,759 deaths. This information belongs to almost 216 Countries, areas, or territories facing COVID-19. The disease trend was not homogeneous across these locations, and studying this variation is a crucial source of information for policymakers and researchers. Therefore, we address different patterns in mortality and incidence of COVID-19 across countries using a clustering approach. Methods: The daily records of new cases and deaths of 216 countries were available on the WHO online COVID-19 dashboard. We used a three-step approach for identifying longitudinal patterns of change in quantitative COVID-19 incidence and mortality rates. At the first, we calculated 27 summary measurements for each trajectory. Then we used factor analysis as a dimension reduction method to capture the correlation between measurements. Finally, we applied a K-means algorithm on the factor scores and clustered the trajectories. Results: We determined three different patterns for the trajectories of COVID-19 incidence and the three different ones for mortality rates. According to incidence rates, among 206 countries the 133 (64.56) countries belong to the second cluster, and 15 (7.28%) and 58 (28.16%) belong to the first and 3rd clusters, respectively. All clusters seem to show an increased rate in the study period, but there are several different patterns. The first one exhibited a mild increasing trend; however, the 3rd and the second clusters followed the severe and moderate increasing trend. According to mortality clusters, the frequency of sets is 37 (18.22%) for the first cluster with moderate increases, 157 (77.34%) for the second one with a mild rise, and 9 (4.34%) for the 3rd one with severe increase. Conclusions: We determined that besides all variations within the countries, the pattern of a contagious disease follows three different trajectories. This variation looks to be a function of the government's health policies more than geographical distribution. Comparing this trajectory to others declares that death is highly related to the nature of epidemy.
MeSH term(s)	COVID-19/epidemiology ; Cluster Analysis ; Factor Analysis, Statistical ; Humans ; Incidence ; Pandemics
Language	English
Publishing date	2022-04-01
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041338-5
ISSN	1471-2458 ; 1471-2458
ISSN (online)	1471-2458
ISSN	1471-2458
DOI	10.1186/s12889-022-13086-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Clustering of countries according to the COVID-19 incidence and mortality rates

Kimiya Gohari / Anoshirvan Kazemnejad / Ali Sheidaei / Sarah Hajari

BMC Public Health, Vol 22, Iss 1, Pp 1-

2022 Volume 12

Abstract: Abstract Background Two years after the beginning of the COVID-19 pandemic on December 29, 2021, there have been 281,808,270 confirmed cases of COVID-19, including 5,411,759 deaths. This information belongs to almost 216 Countries, areas, or territories ... ...

Abstract	Abstract Background Two years after the beginning of the COVID-19 pandemic on December 29, 2021, there have been 281,808,270 confirmed cases of COVID-19, including 5,411,759 deaths. This information belongs to almost 216 Countries, areas, or territories facing COVID-19. The disease trend was not homogeneous across these locations, and studying this variation is a crucial source of information for policymakers and researchers. Therefore, we address different patterns in mortality and incidence of COVID-19 across countries using a clustering approach. Methods The daily records of new cases and deaths of 216 countries were available on the WHO online COVID-19 dashboard. We used a three-step approach for identifying longitudinal patterns of change in quantitative COVID-19 incidence and mortality rates. At the first, we calculated 27 summary measurements for each trajectory. Then we used factor analysis as a dimension reduction method to capture the correlation between measurements. Finally, we applied a K-means algorithm on the factor scores and clustered the trajectories. Results We determined three different patterns for the trajectories of COVID-19 incidence and the three different ones for mortality rates. According to incidence rates, among 206 countries the 133 (64.56) countries belong to the second cluster, and 15 (7.28%) and 58 (28.16%) belong to the first and 3rd clusters, respectively. All clusters seem to show an increased rate in the study period, but there are several different patterns. The first one exhibited a mild increasing trend; however, the 3rd and the second clusters followed the severe and moderate increasing trend. According to mortality clusters, the frequency of sets is 37 (18.22%) for the first cluster with moderate increases, 157 (77.34%) for the second one with a mild rise, and 9 (4.34%) for the 3rd one with severe increase. Conclusions We determined that besides all variations within the countries, the pattern of a contagious disease follows three different trajectories. This variation ...
Keywords	COVID-19 ; Trajectory ; Clustering ; Mortality rate ; Incidence rate ; Public aspects of medicine ; RA1-1270
Subject code	306
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Development of a gastric cancer risk calculator for questionnaire-based surveillance of Iranian dyspeptic patients.

Gohari, Kimiya / Saberi, Samaneh / Esmaieli, Maryam / Tashakoripour, Mohammad / Hosseini, Mahmoud Eshagh / Nahvijou, Azin / Mohagheghi, Mohammad Ali / Kazemnejad, Anoshirvan / Mohammadi, Marjan

BMC gastroenterology

2024 Volume 24, Issue 1, Page(s) 39

Abstract: Background: Gastric cancer (GC) is considered a silent killer, taking more than three quarters of a million lives annually. Therefore, prior to further costly and invasive diagnostic approaches, an initial GC risk screening is desperately in demand.: ... ...

Abstract	Background: Gastric cancer (GC) is considered a silent killer, taking more than three quarters of a million lives annually. Therefore, prior to further costly and invasive diagnostic approaches, an initial GC risk screening is desperately in demand. Methods: In order to develop a simple risk scoring system, the demographic and lifestyle indices from 858 GC and 1132 non-ulcer dyspeptic (NUD) patients were analysed. We applied a multivariate logistic regression approach to identify the association between our target predictors and GC versus NUD. The model performance in classification was assessed by receiver operating characteristic (ROC) analysis. Our questionnaire covering 64 predictors, included known risk factors, such as demographic features, dietary habits, self-reported medical status, narcotics use, and SES indicators. Results: Our model segregated GC from NUD patients with the sensitivity, specificity, and accuracy rates of 85.89, 63.9, and 73.03%, respectively, which was confirmed in the development dataset (AUC equal to 86.37%, P < 0.0001). Predictors which contributed most to our GC risk calculator, based on risk scores (RS) and shared percentages (SP), included: 1) older age group [> 70 (RS:+ 241, SP:7.23), 60-70 (RS:+ 221, SP:6.60), 50-60 (RS:+ 134, SP:4.02), 2) history of gastrointestinal cancers (RS:+ 173, SP:5.19), 3) male gender (RS:+ 119, SP:3.55), 4) non-Fars ethnicity (RS:+ 89, SP:2.66), 5) illiteracy of both parents (RS:+ 78, SP:2.38), 6) rural residence (RS:+ 77, SP:2.3), and modifiable dietary behaviors (RS:+ 32 to + 53, SP:0.96 to 1.58). Conclusion: Our developed risk calculator provides a primary screening step, prior to the subsequent costly and invasive measures. Furthermore, public awareness regarding modifiable risk predictors may encourage and promote lifestyle adjustments and healthy behaviours.
MeSH term(s)	Humans ; Male ; Aged ; Stomach Neoplasms/diagnosis ; Iran ; Dyspepsia/diagnosis ; Surveys and Questionnaires
Language	English
Publishing date	2024-01-18
Publishing country	England
Document type	Journal Article
ZDB-ID	2041351-8
ISSN	1471-230X ; 1471-230X
ISSN (online)	1471-230X
ISSN	1471-230X
DOI	10.1186/s12876-024-03123-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Clear cell carcinoma of the ovary and venous thromboembolism: a systematic review and meta-analysis.

Didar, Hamidreza / Farzaneh, Farah / Najafiarab, Hanieh / Namakin, Kosar / Gohari, Kimiya / Sheidaei, Ali / Ramezani, Sepehr

Current medical research and opinion

2023 Volume 39, Issue 6, Page(s) 901–910

Abstract: Objectives: As the second most common subtype of Epithelial ovarian cancers (EOCs), ovarian clear cell carcinoma (OCCC) is associated with a high rate of cancer-associated thrombosis. Previous studies revealed the wide range prevalence (6-42%) of venous ...

Abstract	Objectives: As the second most common subtype of Epithelial ovarian cancers (EOCs), ovarian clear cell carcinoma (OCCC) is associated with a high rate of cancer-associated thrombosis. Previous studies revealed the wide range prevalence (6-42%) of venous thromboembolism (VTE) among OCCC patients. This study aimed to determine the prevalence of VTE among OCCC patients as well as factors affecting it. Methods: PubMed, Scopus, Embase, and Cochrane Library databases were searched up to December 12 Results: Out of the 2254 records, 43 studies were processed for final review. The qualified studies involved 573 VTE cases among 2965 patients with OCCC. The pooled prevalence of VTE among OCCC patients was 21.32% (95%CI=(17.38-25.87)). Most VTE events were reported in Japanese women (26.15%), followed by Americans (24.41%) and UK (21.57%), and Chinese (13.61%) women. VTE was more common in patients with advanced stages (37.79%) compared to those with early stages of the disease (16.54%). Conclusions: Ovarian clear cell carcinoma is associated with a high rate of cancer-associated thrombosis. VTE events in OCCC patients were higher in advanced stages and Japanese women.
MeSH term(s)	Humans ; Female ; Male ; Venous Thromboembolism/epidemiology ; Venous Thromboembolism/etiology ; Ovary ; Risk Factors ; Venous Thrombosis ; Carcinoma
Language	English
Publishing date	2023-05-07
Publishing country	England
Document type	Meta-Analysis ; Systematic Review ; Journal Article ; Review
ZDB-ID	80296-7
ISSN	1473-4877 ; 0300-7995
ISSN (online)	1473-4877
ISSN	0300-7995
DOI	10.1080/03007995.2023.2208488
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 955: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: A Bayesian latent class extension of naive Bayesian classifier and its application to the classification of gastric cancer patients.

Gohari, Kimiya / Kazemnejad, Anoshirvan / Mohammadi, Marjan / Eskandari, Farzad / Saberi, Samaneh / Esmaieli, Maryam / Sheidaei, Ali

BMC medical research methodology

2023 Volume 23, Issue 1, Page(s) 190

Abstract: Background: The Naive Bayes (NB) classifier is a powerful supervised algorithm widely used in Machine Learning (ML). However, its effectiveness relies on a strict assumption of conditional independence, which is often violated in real-world scenarios. ... ...

Abstract	Background: The Naive Bayes (NB) classifier is a powerful supervised algorithm widely used in Machine Learning (ML). However, its effectiveness relies on a strict assumption of conditional independence, which is often violated in real-world scenarios. To address this limitation, various studies have explored extensions of NB that tackle the issue of non-conditional independence in the data. These approaches can be broadly categorized into two main categories: feature selection and structure expansion. In this particular study, we propose a novel approach to enhancing NB by introducing a latent variable as the parent of the attributes. We define this latent variable using a flexible technique called Bayesian Latent Class Analysis (BLCA). As a result, our final model combines the strengths of NB and BLCA, giving rise to what we refer to as NB-BLCA. By incorporating the latent variable, we aim to capture complex dependencies among the attributes and improve the overall performance of the classifier. Methods: Both Expectation-Maximization (EM) algorithm and the Gibbs sampling approach were offered for parameter learning. A simulation study was conducted to evaluate the classification of the model in comparison with the ordinary NB model. In addition, real-world data related to 976 Gastric Cancer (GC) and 1189 Non-ulcer dyspepsia (NUD) patients was used to show the model's performance in an actual application. The validity of models was evaluated using the 10-fold cross-validation. Results: The presented model was superior to ordinary NB in all the simulation scenarios according to higher classification sensitivity and specificity in test data. The NB-BLCA model using Gibbs sampling accuracy was 87.77 (95% CI: 84.87-90.29). This index was estimated at 77.22 (95% CI: 73.64-80.53) and 74.71 (95% CI: 71.02-78.15) for the NB-BLCA model using the EM algorithm and ordinary NB classifier, respectively. Conclusions: When considering the modification of the NB classifier, incorporating a latent component into the model offers numerous advantages, particularly within medical and health-related contexts. By doing so, the researchers can bypass the extensive search algorithm and structure learning required in the local learning and structure extension approach. The inclusion of latent class variables allows for the integration of all attributes during model construction. Consequently, the NB-BLCA model serves as a suitable alternative to conventional NB classifiers when the assumption of independence is violated, especially in domains pertaining to health and medicine.
MeSH term(s)	Humans ; Stomach Neoplasms/diagnosis ; Bayes Theorem ; Algorithms ; Computer Simulation ; Machine Learning
Language	English
Publishing date	2023-08-21
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041362-2
ISSN	1471-2288 ; 1471-2288
ISSN (online)	1471-2288
ISSN	1471-2288
DOI	10.1186/s12874-023-02013-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: A novel dynamic Bayesian network approach for data mining and survival data analysis.

Sheidaei, Ali / Foroushani, Abbas Rahimi / Gohari, Kimiya / Zeraati, Hojjat

BMC medical informatics and decision making

2022 Volume 22, Issue 1, Page(s) 251

Abstract: Background: Censorship is the primary challenge in survival modeling, especially in human health studies. The classical methods have been limited by applications like Kaplan-Meier or restricted assumptions like the Cox regression model. On the other ... ...

Abstract	Background: Censorship is the primary challenge in survival modeling, especially in human health studies. The classical methods have been limited by applications like Kaplan-Meier or restricted assumptions like the Cox regression model. On the other hand, Machine learning algorithms commonly rely on the high dimensionality of data and ignore the censorship attribute. In addition, these algorithms are more sophisticated to understand and utilize. We propose a novel approach based on the Bayesian network to address these issues. Methods: We proposed a two-slice temporal Bayesian network model for the survival data, introducing the survival and censorship status in each observed time as the dynamic states. A score-based algorithm learned the structure of the directed acyclic graph. The likelihood approach conducted parameter learning. We conducted a simulation study to assess the performance of our model in comparison with the Kaplan-Meier and Cox proportional hazard regression. We defined various scenarios according to the sample size, censoring rate, and shapes of survival and censoring distributions across time. Finally, we fit the model on a real-world dataset that includes 760 post gastrectomy surgery due to gastric cancer. The validation of the model was explored using the hold-out technique based on the posterior classification error. Our survival model performance results were compared using the Kaplan-Meier and Cox proportional hazard models. Results: The simulation study shows the superiority of DBN in bias reduction for many scenarios compared with Cox regression and Kaplan-Meier, especially in the late survival times. In the real-world data, the structure of the dynamic Bayesian network model satisfied the finding from Kaplan-Meier and Cox regression classical approaches. The posterior classification error found from the validation technique did not exceed 0.04, representing that our network predicted the state variables with more than 96% accuracy. Conclusions: Our proposed dynamic Bayesian network model could be used as a data mining technique in the context of survival data analysis. The advantages of this approach are feature selection ability, straightforward interpretation, handling of high-dimensional data, and few assumptions.
MeSH term(s)	Algorithms ; Bayes Theorem ; Data Analysis ; Data Mining ; Humans ; Likelihood Functions ; Proportional Hazards Models ; Survival Analysis
Language	English
Publishing date	2022-09-22
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2046490-3
ISSN	1472-6947 ; 1472-6947
ISSN (online)	1472-6947
ISSN	1472-6947
DOI	10.1186/s12911-022-02000-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: The 15-year national trends of urinary cancers incidence among Iranian men and women; 2005-2020.

Mousavian, Amir-Hossein / Shafiee, Gita / Sheidaei, Ali / Balajam, Narges Zargar / Ebrahimi, Mehdi / Khatami, Fatemeh / Gohari, Kimiya / Aryan, Alisam / Ghanbari-Motlagh, Ali / Ostovar, Afshin / Aghamir, Seyed Mohammad Kazem / Heshmat, Ramin

International journal for equity in health

2024 Volume 23, Issue 1, Page(s) 13

Abstract: Background: Urinary tract cancers including bladder, kidney, ureter, and pelvis are a common malignancy worldwide with high mortality ratio. Aimed to investigate the prevalence of these cancers, we conducted this study.: Methods: In this study, all ... ...

Abstract	Background: Urinary tract cancers including bladder, kidney, ureter, and pelvis are a common malignancy worldwide with high mortality ratio. Aimed to investigate the prevalence of these cancers, we conducted this study. Methods: In this study, all the information related to ICD10 codes, gender, age and province of residence of individuals were obtained from the data of Iran's cancer registry by the Ministry of Health, Medicine and Medical Education and demographic evidence for each sub-country from the reports of Statistics Center of Iran (SCI). Also, the data of two Iranian national survey studies CASPIAN-III, IV, and V (information related to the care and prevention of non-communicable diseases (NCD) in childhood and adolescence) and STEPs (including information on NCD in adults over 18 years old) were used. The data was analyzed using Poisson regression with mixed effects to estimate the incidence of cancers. Results: Bladder and kidney neoplasm are the most common cancers of the urinary system in Iran. The prevalence of bladder cancer has increased from 5.82 to 11.50 per 100,000 individuals. The increasing trend is growing faster in men compared with women. The incidence of kidney neoplasm has increased over the years (2.03 in 2005 vs. 7.02 in 2020 per 100,000). Having a higher incidence ratio compared with bladder cancer, kidney cancer is responsible for 35.06% of all urinary cancers in 2020 compared with 23.71% in 2005. Both neoplasms of the ureter and renal pelvis were recorded rarely and with lower incidence in both sexes during this period. Conclusion: Considering the increasing trend in the incidence of urinary neoplasms in Iran during these years, the advantage of focusing on the risk of urinary cancers is highlighted. Therefore, investigating the prevalence and incidence of urinary cancers to plan and manage these cancers will result in prevention and reduction of the disease burden on the Iranian society. Future studies in this field can help in the prevention and well-timed diagnosis of these cancers.
MeSH term(s)	Adolescent ; Adult ; Male ; Female ; Humans ; Iran/epidemiology ; Incidence ; Noncommunicable Diseases ; Urologic Neoplasms ; Urinary Bladder Neoplasms/epidemiology ; Kidney Neoplasms
Language	English
Publishing date	2024-01-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2092056-8
ISSN	1475-9276 ; 1475-9276
ISSN (online)	1475-9276
ISSN	1475-9276
DOI	10.1186/s12939-023-02084-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Diagnostic performance of classification trees and hematological functions in hematologic disorders: an application of multidimensional scaling and cluster analysis.

Rahim, Fakher / Kazemnejad, Anoshirvan / Jahangiri, Mina / Malehi, Amal Saki / Gohari, Kimiya

BMC medical informatics and decision making

2021 Volume 21, Issue 1, Page(s) 313

Abstract: Background: Several hematological indices have been already proposed to discriminate between iron deficiency anemia (IDA) and β-thalassemia trait (βTT). This study compared the diagnostic performance of different hematological discrimination indices ... ...

Abstract	Background: Several hematological indices have been already proposed to discriminate between iron deficiency anemia (IDA) and β-thalassemia trait (βTT). This study compared the diagnostic performance of different hematological discrimination indices with decision trees and support vector machines, so as to discriminate IDA from βTT using multidimensional scaling and cluster analysis. In addition, decision trees were used to determine the diagnostic classification scheme of patients. Methods: Consisting of 1178 patients with hypochromic microcytic anemia (708 patients with βTT and 470 patients with IDA), this cross-sectional study compared the diagnostic performance of 43 hematological discrimination indices with classification tree algorithms and support vector machines in order to discriminate IDA from βTT. Moreover, multidimensional scaling and cluster analysis were used to identify the homogeneous subgroups of discrimination methods with similar performance. Results: All the classification tree algorithms except the LOTUS tree algorithm showed acceptable accuracy measures for discrimination between IDA and βTT in comparison with other hematological discrimination indices. The results indicated that the CRUISE and C5.0 tree algorithms had better diagnostic performance and efficiency among other discrimination methods. Moreover, the AUC of CRUISE and C5.0 tree algorithms indicated more precise classification with values of 0.940 and 0.999, indicating excellent diagnostic accuracy of such models. Moreover, the CRUISE and C5.0 tree algorithms showed that mean corpuscular volume can be considered as the main variable in discrimination between IDA and βTT. Conclusions: CRUISE and C5.0 tree algorithms as powerful methods in data mining techniques can be used to develop accurate differential methods along with other laboratory parameters for the discrimination of IDA and βTT. In addition, the multidimensional scaling method and cluster analysis can be considered as the most appropriate techniques to determine the discrimination indices with similar performance for future hematological studies.
MeSH term(s)	Anemia, Iron-Deficiency/diagnosis ; Cluster Analysis ; Cross-Sectional Studies ; Diagnosis, Differential ; Humans ; Multidimensional Scaling Analysis
Language	English
Publishing date	2021-11-10
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2046490-3
ISSN	1472-6947 ; 1472-6947
ISSN (online)	1472-6947
ISSN	1472-6947
DOI	10.1186/s12911-021-01678-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito