Analysis of Diabetic Patients' Data for Clustering and Prescription Drug Based on Proposed Algorithm

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Heidari Safanaz; RADFAR REZA; ALBORZI MAHMOOD; AFSHAR KAZEMI MOHAMMAD ALI; RAJABZADEH GHATARI ALI

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Journal: Medical Journal of Mashhad University of Medical Sciences Year:2020 | Volume:63 | Issue:2 Page(s): 2358-2368

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Title

Analysis of Diabetic Patients' Data for Clustering and Prescription Drug Based on Proposed Algorithm

Author(s)

Keywords

Data mining

clustering

Hadoop

Map-Reduce

Big data

diabetic

Abstract

Introduction: Diabetes is a metabolic disorder in the body that is impaired by the ability to produce insulin hormone. The main purpose of the present study is to discover the hidden knowledge in the data of diabetic patients, which can assist clinicians in clustering new patients and prescribing appropriate medication according to each cluster. Materials and Methods: In this paper, we use MR-VDBSCAN algorithm. The implementation of this algorithm is based on the Map-Reduce framework of Hadoop. The main idea of the research is to use local density to find the density of each point. This strategy can prevent clusters from joining at different densities. Results: The algorithm is based on the selected dataset, tested and evaluated, and the results show high accuracy and efficiency. The results were compared with the results of k-Means clustering, The MR-VDBSCAN algorithm has a higher execution speed than that of the algorithm and has the ability to detect clusters with different density of superiority of this algorithm than the comparable algorithm. The results show that the MRVDBSCAN algorithm can provide better performance than other algorithms. In particular, the similarity of the proposed algorithm is 97% for the diabetes set. Conclusion: The results show that the MR-VDBSCAN algorithm performs better clustering than the K-means algorithm and can place patients into subgroups that assist physicians in prescribing.

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APA: Copy

Heidari, Safanaz, RADFAR, REZA, ALBORZI, MAHMOOD, AFSHAR KAZEMI, MOHAMMAD ALI, & RAJABZADEH GHATARI, ALI. (2020). Analysis of Diabetic Patients' Data for Clustering and Prescription Drug Based on Proposed Algorithm. MEDICAL JOURNAL OF MASHHAD UNIVERSITY OF MEDICAL SCIENCES, 63(2 ), 2358-2368. SID. https://sid.ir/paper/950125/en

Vancouver: Copy

Heidari Safanaz, RADFAR REZA, ALBORZI MAHMOOD, AFSHAR KAZEMI MOHAMMAD ALI, RAJABZADEH GHATARI ALI. Analysis of Diabetic Patients' Data for Clustering and Prescription Drug Based on Proposed Algorithm. MEDICAL JOURNAL OF MASHHAD UNIVERSITY OF MEDICAL SCIENCES[Internet]. 2020;63(2 ):2358-2368. Available from: https://sid.ir/paper/950125/en

IEEE: Copy

Safanaz Heidari, REZA RADFAR, MAHMOOD ALBORZI, MOHAMMAD ALI AFSHAR KAZEMI, and ALI RAJABZADEH GHATARI, “Analysis of Diabetic Patients' Data for Clustering and Prescription Drug Based on Proposed Algorithm,” MEDICAL JOURNAL OF MASHHAD UNIVERSITY OF MEDICAL SCIENCES, vol. 63, no. 2 , pp. 2358–2368, 2020, [Online]. Available: https://sid.ir/paper/950125/en

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