An intelligent approach to discovering common symptoms among depressed patients

Verfasser / Beitragende:
[Yusra Ghafoor, Yo-Ping Huang, Shen-Ing Liu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/4(2015-04-01), 819-827
Format:
Artikel (online)
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024 7 0 |a 10.1007/s00500-014-1408-4  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00500-014-1408-4 
245 0 3 |a An intelligent approach to discovering common symptoms among depressed patients  |h [Elektronische Daten]  |c [Yusra Ghafoor, Yo-Ping Huang, Shen-Ing Liu] 
520 3 |a On world's health care radar, one of the emerging fatal diseases is depression. Mainly young generation is becoming victim to this because of the fast pace of life. Extensive measures should be taken to overcome this trauma. Data are collected worldwide to gain some useful knowledge, but problem occurs in handling the large amount of data. Therefore, data mining techniques are being used to resolve the problems. In this paper, we have applied the data mining techniques such as association analysis and frequent pattern tree on depression database containing 5,964 records. These techniques are used altogether to extract efficient results. It saves the processing time and effort when used together. The results from our analysis state the most common symptoms of depressed patients as well as discuss the scenarios of the patients. The limitations of the suggested techniques help make an inference that how fuzzy concept is more beneficial in the given situation. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a Depression  |2 nationallicence 
690 7 |a Data mining  |2 nationallicence 
690 7 |a Association rules  |2 nationallicence 
690 7 |a FP tree  |2 nationallicence 
700 1 |a Ghafoor  |D Yusra  |u Department of Electrical Engineering, National Taipei University of Technology, 10608, Taipei, Taiwan  |4 aut 
700 1 |a Huang  |D Yo-Ping  |u Department of Electrical Engineering, National Taipei University of Technology, 10608, Taipei, Taiwan  |4 aut 
700 1 |a Liu  |D Shen-Ing  |u Department of Psychiatry, Mackay Memorial Hospital, 10449, Taipei, Taiwan  |4 aut 
773 0 |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/4(2015-04-01), 819-827  |x 1432-7643  |q 19:4<819  |1 2015  |2 19  |o 500 
856 4 0 |u https://doi.org/10.1007/s00500-014-1408-4  |q text/html  |z Onlinezugriff via DOI 
898 |a BK010053  |b XK010053  |c XK010000 
900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00500-014-1408-4  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Ghafoor  |D Yusra  |u Department of Electrical Engineering, National Taipei University of Technology, 10608, Taipei, Taiwan  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Huang  |D Yo-Ping  |u Department of Electrical Engineering, National Taipei University of Technology, 10608, Taipei, Taiwan  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Liu  |D Shen-Ing  |u Department of Psychiatry, Mackay Memorial Hospital, 10449, Taipei, Taiwan  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/4(2015-04-01), 819-827  |x 1432-7643  |q 19:4<819  |1 2015  |2 19  |o 500