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Paper Information

Journal:   HEALTH INFORMATION MANAGEMENT   OCTOBER-NOVEMBER2012 , Volume 9 , Number 4; Page(s) 457 To 464.
 
Paper: 

DESIGNING A CLINICAL DECISION SUPPORT SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK FOR EARLY DETECTION OF PROSTATE CANCER AND DIFFERENTIATION FROM BENIGN PROSTATIC HYPERPLASIA

 
 
Author(s):  GHADERZADEH MUSTAFA, SADOUGHI FARAHNAZ*, KETABAT ARVIN
 
* SCHOOL OF HEALTH MANAGEMENT AND INFORMATION SCIENCES, TEHRAN UNIVERSITY OF MEDICAL SCIENCES, TEHRAN, IRAN
 
Abstract: 

Introduction: In recent years, the concepts of artificial neural networks (ANN) have extensively undergone remarkable development in early detection and classification of diseases such as benign prostatic hyperplasia (BPH). The usage of ANN has become widely accepted in medical applications owing to its potential capabilities for detecting the complex interactions among variables, diagnosis and diseases’ modeling. The present study aimed to design and implement a decision support system (DSS) based on ANN for early detection of prostate cancer.
Methods: This survey design was conducted through data collection among 360 males with prostate abnormalities in Urology Department of Imam Khomeini Hospital, Tehran, Iran, from January 2008 to March 2011. In order to assess the performance and accuracy of the designed system, sensitivity, specificity and receiver-operating characteristics (ROC) curve were used as the indicators of distinguishing prostate cancers from BPH. In order to implement DSS in this study, scaled conjugate gradient (SCG) algorithm was used as the main algorithm for early detection of prostate cancer from benign prostate.
Results: The proposed intelligent ANN-based system can be used as a strong diagnostic tool with 97.0% specificity and 92.1% sensitivity for detecting the prostate cancer and to differentiate it from BPH. The results indicated a high potential of artificial neural network as a strong tool in classification of prostatic neoplasia diseases.
Conclusion: A medical decision support system was used aiming to help medical experts in their classification and early detection of prostatic neoplasia disorders in the present study. Such artificial intelligent-based medical intelligent systems, particularly for neural networks, can help physicians in accurate decision-making concerning prostate cancer and BPH. Using such systems, specialists would be able to eliminate or minimize unnecessary biopsy and reduce diagnostic costs. In addition, such systems can accelerate the diagnostic detection time.

 
Keyword(s): DECISION SUPPORT SYSTEM, PROSTATIC NEOPLASIA, ARTIFICIAL NEURAL NETWORK, SENSITIVITY, SPECIFICITY
 
 
References: 
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Click to Cite.
APA: Copy

GHADERZADEH, M., & SADOUGHI, F., & KETABAT, A. (2012). DESIGNING A CLINICAL DECISION SUPPORT SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK FOR EARLY DETECTION OF PROSTATE CANCER AND DIFFERENTIATION FROM BENIGN PROSTATIC HYPERPLASIA. HEALTH INFORMATION MANAGEMENT, 9(4), 457-464. https://www.sid.ir/en/journal/ViewPaper.aspx?id=403474



Vancouver: Copy

GHADERZADEH MUSTAFA, SADOUGHI FARAHNAZ, KETABAT ARVIN. DESIGNING A CLINICAL DECISION SUPPORT SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK FOR EARLY DETECTION OF PROSTATE CANCER AND DIFFERENTIATION FROM BENIGN PROSTATIC HYPERPLASIA. HEALTH INFORMATION MANAGEMENT. 2012 [cited 2021May11];9(4):457-464. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=403474



IEEE: Copy

GHADERZADEH, M., SADOUGHI, F., KETABAT, A., 2012. DESIGNING A CLINICAL DECISION SUPPORT SYSTEM BASED ON ARTIFICIAL NEURAL NETWORK FOR EARLY DETECTION OF PROSTATE CANCER AND DIFFERENTIATION FROM BENIGN PROSTATIC HYPERPLASIA. HEALTH INFORMATION MANAGEMENT, [online] 9(4), pp.457-464. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=403474.



 
 
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