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Similarity Analysis of Patients’ Data: Bangladesh Perspective
International Conference on Medical Engineering, Health Informatics and Technology (MediTec 2016) (2016)
  • Shahidul Islam Khan, Bangladesh University of Engineering and Technology
  • Abu Sayed Md. Latiful Hoque, Bangladesh University of Engineering and Technology
Abstract
Misspelling of names is a major problem of real world datasets and a single person is identified differently as its consequence. In Bangladesh, it is common that many people, in real, do not know their full name and many of Bangladeshi citizens are unable to pronounce their name correctly, even in the mother tongue.  The Same person provides a different version of their name during taking a public service e.g., treatment in hospital. In the practical situations at most health centers, patients are asked and they tell their information i.e. name, age verbally. This creates ambiguity with misspelled names. In this paper, we have provided an algorithm to identify the same person correctly from the variation of names. Experimental results show that our proposed technique can successfully link records with high accuracy for noisy data like misspelled patient names etc.
Keywords
  • Record Linkage,
  • Name,
  • Bangladesh,
  • Phonetic Analysis,
  • Health Data
Publication Date
December 17, 2016
Citation Information
Shahidul Islam Khan and Abu Sayed Md. Latiful Hoque. "Similarity Analysis of Patients’ Data: Bangladesh Perspective" International Conference on Medical Engineering, Health Informatics and Technology (MediTec 2016) (2016)
Available at: http://works.bepress.com/shahidulislam-khan/9/