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Featured researches published by Rade Prelevic.


Expert Systems With Applications | 2014

Evolutionary assembled neural networks for making medical decisions with minimal regret: Application for predicting advanced bladder cancer outcome

Arso M. Vukicevic; Gordana R. Jovicic; Miroslav Stojadinovic; Rade Prelevic; Nenad Filipovic

Abstract Development of reliable medical decision support systems has been the subject of many studies among which Artificial Neural Networks (ANNs) gained increasing popularity and gave promising results. However, wider application of ANNs in clinical practice remains limited due to the lack of a standard and intuitive procedure for their configuration and evaluation which is traditionally a slow process depending on human experts. The principal contribution of this study is a novel procedure for obtaining ANN predictive models with high performances. In order to reach those considerations with minimal user effort, optimal configuration of ANN was performed automatically by Genetic Algorithms (GA). The only two user dependent tasks were selecting data (input and output variables) and evaluation of ANN threshold probability with respect to the Regret Theory (RT). The goal of the GA optimization was reaching the best prognostic performances relevant for clinicians: correctness, discrimination and calibration. After optimally configuring ANNs with respect to these criteria, the clinical usefulness was evaluated by the RT Decision Curve Analysis. The method is initially proposed for the prediction of advanced bladder cancer (BC) in patients undergoing radical cystectomy, due to the fact that it is clinically relevant problem with profound influence on health care. Testing on the data of the ten years cohort study, which included 183 evaluable patients, showed that soft max activation functions and good calibration were the most important for obtaining reliable BC predictive models for the given dataset. Extensive analysis and comparison with the solutions commonly used in literature showed that better prognostic performances were achieved while user-dependency was significantly reduced. It is concluded that presented procedure represents a suitable, robust and user-friendly framework with potential to have wide applications and influence in further development of health care decision support systems.


Vojnosanitetski Pregled | 2015

The clinical course of non-muscle invasive bladder cancer after transurethral resection of the tumor with or without subsequent intravesical application of bacillus Calmette-Guérin: The influence of patients gender and age.

Radovan Milosevic; Novak Milovic; Predrag Aleksic; Miodrag Lazic; Rade Prelevic; Aleksandar Spasic; Dejan Simic; Bozidar Kovacevic

UNLABELLED BACGROUND/AIM: The therapy with intravesical instillation of bacillus Calmette-Guérin (BCG) after transurethral resection (TUR) of tumor is the gold standard of treatment of non-muscle invasive bladder cancer (NMIBC). The role and importance of BCG intravesical therapy in various shape of tumors, were confirmed by our previous investigation. The aim of this study was to examine whether incidence of recurrence and tumor regression differs depending on sex and age of patients. METHODS This study included a total of 899 patients suffering from NIMBC, treated at our institution from January 1, 2007 to March 1, 2013. Two groups of patients were formed: patients underwent TUR + BCG therapy (the group I) and the group II with patients in whom TUR was performed as only therapy. These two groups of patients were divided into subgroups of respondents male and female, age 60 years or younger and older than 60 years. Statistical analysis was performed using χ2 test and the Kolmogorov-Smirnov test. RESULTS This research suggests that if the frequency of recurrence is seen as the only parameter, considering all the subjects, the lowest recurrence rate was determined in the male subjects, aged 60 years and younger who had received BCG after TUR. A high statistical significance was found in the incidence of recurrence in patients younger than 60 years, depending on the response to the therapy, while in those older than 60 years, the difference was at the level of statistical significance. This can be attributed to a certain degree of infravesical obstruction in older men. CONCLUSIONS Sex and age of patients may have a significant influence on the course and outcome of NMIBC. The disease has the most malignant and most aggressive behavior when present in males older than 60 years.


Vojnosanitetski Pregled | 2014

Scoring system development for prediction of extravesical bladder cancer.

Rade Prelevic; Miroslav Stojadinovic; Dejan Simic; Aleksandar Spasic; Nikola Petrović


International Urology and Nephrology | 2014

Scoring system for prediction of lymph node metastasis in radical cystectomy cohort

Miroslav Stojadinovic; Rade Prelevic; Arso M. Vukicevic


publisher | None

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Vojnosanitetski Pregled | 2017

Abdominal localization of unicentric form of Castleman disease: A case report

Bosko Milev; Borka Milev; Zoran Kostic; Darko Mirkovic; Nenad Perisic; Olga Tasic; Marija Elez; Aleksandar Radunovic; Milan Jovanovic; Predrag Maric; Sanja Daisevic; Rade Prelevic; Maja Vulovic


Vojnosanitetski Pregled | 2016

The frequency of metabolic syndrome in patients with the subclinical hypothyroidism

Mersudin Mulic; Fadil Skrijeljm; Sefcet Hajrovic; Rade Prelevic; Bosko Milev


Vojnosanitetski Pregled | 2016

Gigantic spermatocytic seminoma: A rare tumor of germ cell origin

Rade Prelevic; Bosko Milev; Novak Milovic; Mihajlo Ignjatović; Aleksandar Spasic; Nikola Petrović


Vojnosanitetski Pregled | 2015

Unrecognised adrenergic symptoms and the delayed diagnosis of urinary bladder paraganglioma.

Tamara Dragovic; Dejan Marinkovic; Snezana Kuzmic-Jankovic; Rade Prelevic; Novak Milovic; Bozidar Kovacevic; Zoran Hajdukovic


International Journal of Clinical Oncology | 2015

External validation of existing nomograms predicting lymph node metastases in cystectomized patients.

Miroslav Stojadinovic; Rade Prelevic

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Novak Milovic

Military Medical Academy

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Darko Mirkovic

Military Medical Academy

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Marija Elez

Military Medical Academy

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