Decision support system for diagnosis and prediction of chronic renal failure using random subspace classification

2016 ◽  
Author(s):  
R Ani ◽  
Greeshma Sasi ◽  
U Resmi Sankar ◽  
O. S. Deepa
Keyword(s):  
Renal Failure ◽  
Decision Support ◽  
Chronic Renal Failure ◽  
Decision Support System ◽  
Support System ◽  
Random Subspace

Diagnosis and Classification of Chronic Renal Failure Utilising Intelligent Data Mining Classifiers

2014 ◽  
Vol 9 (4) ◽  
pp. 1-12 ◽  
Author(s):  
Abeer Y. Al-Hyari ◽  
Ahmad M. Al-Taee ◽  
Majid A. Al-Taee
Keyword(s):  
Data Mining ◽  
Renal Failure ◽  
Decision Support ◽  
Chronic Renal Failure ◽  
Decision Support System ◽  
Support System ◽  
Clinical Decision ◽  
Support Vector ◽  
Artificial Neural Network Ann ◽  
Sensitivity Specificity

This paper presents a new clinical decision support system for diagnosing patients with Chronic Renal Failure (CRF) which is not yet thoroughly explored in literature. This paper aims at improving performance of a previously reported CRF diagnosis system which was based on Artificial Neural Network (ANN), Decision Tree (DT) and Naïve Bayes (NB) classifying algorithms. This is achieved by utilizing more efficient data mining classifiers, Support Vector Machine (SVM) and Logistic Regression (LR), in order to: (i) diagnose patients with CRF and (ii) determine the rate at which the disease is progressing. A clinical dataset of more than 100 instances is used in this study. Performance of the developed decision support system is assessed in terms of diagnostic accuracy, sensitivity, specificity and decisions made by consultant specialist physicians. The open source Waikato Environment for Knowledge Analysis library is used in this study to build and evaluate performance of the developed data mining classifiers. The obtained results showed SVM to be the most accurate (93.14%) when compared to LR as well as other classifiers reported in the previous study. A complete system prototype has been developed and tested successfully with the aid of NHS collaborators to support both diagnosis and long-term management of the disease.

Impact of a clinical decision support system for drug dosage in patients with renal failure

2018 ◽  
Vol 40 (5) ◽  
pp. 1225-1233 ◽  
Author(s):  
Sophie Desmedt ◽  
Anne Spinewine ◽  
Michel Jadoul ◽  
Séverine Henrard ◽  
Dominique Wouters ◽  
...  
Keyword(s):  
Renal Failure ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Drug Dosage

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

THE ACCURACY OF THE SPORTS TALENT IDENTIFICATION DECISION SUPPORT SYSTEM FOR YOUNG ATHLETES

2014 ◽  
Author(s):  
Kamaruzaman S. ◽  
◽  
A. H. Omar ◽  
Muhammad Iqbal Tariq Idris ◽  
Izwyn Z. ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Young Athletes ◽  
Talent Identification ◽  
Identification Decision
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