Majlinda, Fetaji and Loku, Lindita and Fetaji, Bekim and Krstev, Aleksandar and Zdravev, Zoran (2019) Application of Data Analytics with Python Programming In Healthcare. South East European Journal of Sustainable Development, 3 (2). pp. 27-31. ISSN 2545-4463
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Abstract
The goal of this research is to investigate how using data analytics and programming python platform can
discover additional value from health information used in health care. Dominant part of the Healthcare
information is frequently unstructured, exists in storehouses and dwells in imaging frameworks, clinical
solution notes, patient information and so forth coordinating these heterogeneous information and calculating
it in to progress investigation is basic to improve medical services results. The incorporation of health sector
data analytics provides stakeholders with fresh perspectives that can advance personalized treatment,
optimize patient outcomes and prevent excessive costs. Until now, medical healthcare has not completely
gotten a handle on the possible advantages to be picked up from information examination. The developing
medical care industry is creating an enormous volume of valuable information on tolerant socioeconomics,
therapy plans, instalment, and protection inclusion pulling in the consideration of clinicians and researchers
the same. Lately, various companion explored articles have tended to various components of information
science application in medical care. Be that as it may, the absence of a thorough and methodical account
roused us to build a study examinations on this field. This examination study characterizes information
investigation and its qualities, remarks on its favourable circumstances and difficulties in medical care.
Information examination gives new systematic open doors as well as faces parcel of difficulties. The research
study begins from investigating the patient information. While picking the stage, a few rules like accessibility,
usability, adaptability, level of security and coherence ought to be thought of. Analyses of all challenges of
data analytics are analyzed and insights are represented and discussed and argumented.
Item Type: | Article |
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Subjects: | Natural sciences > Computer and information sciences |
Divisions: | Faculty of Computer Science |
Depositing User: | Aleksandar Velinov |
Date Deposited: | 04 Feb 2021 09:10 |
Last Modified: | 04 Feb 2021 09:10 |
URI: | https://eprints.ugd.edu.mk/id/eprint/27484 |
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