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Complete Blood Analysis: An Android OCR-Based Interpretation

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Intelligent Computing (SAI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 507))

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Abstract

Complete Blood Count (CBC) test is part of the routine medical care for many people. It can uncover serious health problems such as anemia, infection, and even blood cancer. However, CBC results are normally presented in English and contain medical abbreviations. This make CBC results hard to understand especially for patients who do not speak English or lack knowledge of medical abbreviations meanings. This paper aims at developing an Android application that helps patients to view, interpret and understand their CBC result in a user-friendly manner. The application employs Optical Character Recognition technology (OCR) that allows patients to scan their CBC results, extract, interpret and translate to Arabic (if needed) the medical information contained in these results. It can also provide patients with the ability to store records of their CBC results for future retrieval and comparison analysis. This study is meant to maximize patients’ awareness about their health conditions based on their CBC result and suggest the measures to be taken in that regard. Experimental results show the developed system can gain 92.48% accuracy for counting the CBC.

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References

  1. MedicineNet.com: [Online]. Available: https://www.medicinenet.com/complete_blood_count/article.htm. Accessed October 2018

  2. Web MD: [Online]. Available: https://www.webmd.com/cancer/lymphoma/symptomswatch-for#1. Accessed October 2018

  3. Wikipedia: [Online]. Available: https://en.wikipedia.org/wiki/Optical_character_recognition#Character_recognition. Accessed October 2018

  4. O.C.S.P. Ltd.: App Store Preview. [Online]. Available: https://itunes.apple.com/us/app/blood-test-guide/id491681195?mt=8. Accessed October 2018

  5. L. Evolve Medical Systems: App Store Preview. [Online]. Available: https://itunes.apple.com/us/app/blood-pressure-smart-blood/id519076558?mt=8. Accessed October 2018

  6. I.F. Studio: iCare Health Monitor. [Online]. Available: http://www.icarefit.com/. Accessed October 2018

  7. M. Apps: App Store Preview. [Online]. Available: https://itunes.apple.com/us/app/medical-lab-tests/id307829594?mt=8. Accessed October 2018

  8. A.A.f.C. Chemistry: Lab Tests Online. [Online]. Available: https://labtestsonline.org/. Accessed October 2018

  9. Seuge Technologies: [Online]. Available: https://www.seguetech.com/8-benefits-ofagile-software-development/. Accessed October 2018

  10. L. SEO: “LINCHPINSEO” [Online]. Available: https://linchpinseo.com/the-agilemethod/. Accessed October 2018

  11. Antaes: [Online]. Available: https://www.antaes.ch/en/news/antaes-asia-is-trained-inagile/. Accessed October 2018

  12. Google: Google Developers. [Online]. Accessed November 2018

    Google Scholar 

  13. Hamouda, S.K.M., Wahed, M.E., Abo Alez, R.H., Riad, K.: Robust breast cancer prediction system based on rough set theory at National Cancer Institute of Egypt. Comp. Methods and Programs in Biomedicine 153, 259–268 (2018)

    Google Scholar 

  14. Hamouda, S.K.M., Abo El-Ezz, R.H., Wahed, M.E.: Enhancement accuracy of breast tumor diagnosis in digital mammograms. J. Biomed. Sci. 6(4), 28 (2017). ISSN 2254-609X

    Google Scholar 

  15. Hamouda, S.K.M., Abo El-Ezz, H.R., Wahed, M.E.: Intelligent system for predicting, diagnosis and treatment of breast cancer. Int. J. Biomed. Data Mining 6, 2 (2017). https://doi.org/10.4172/2090-4924.1000128

  16. Atlam, E.-S., Fuketa, M., Morita, K., Aoe, J.: Document similarity measurement using field association term. Info. Proce. Manage. J. 39(6), pp. 809–824 (2003)

    Google Scholar 

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Correspondence to Elsayed Atlam .

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Almaliki, M., Atlam, E. (2022). Complete Blood Analysis: An Android OCR-Based Interpretation. In: Arai, K. (eds) Intelligent Computing. SAI 2022. Lecture Notes in Networks and Systems, vol 507. Springer, Cham. https://doi.org/10.1007/978-3-031-10464-0_18

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