Proceedings of the 2015 International Conference on Recent Advances in Computer Systems

Estimating Diabetic cases in KSA through search trends and Creating Cyber Diabetic Community.

Authors
Yasir Javed, Adnan Khan, Basit Qureshi, Junaid Chaudhry
Corresponding Author
Yasir Javed
Available Online November 2015.
DOI
https://doi.org/10.2991/racs-15.2016.30How to use a DOI?
Keywords
Prediction of Diabetes, Google Trends, Correlation of healthcare data, Cyber diabetic community
Abstract
Saudi Arabia is fastest developing nation enjoying stability and high per capita income, thus highly influenced by urbanization inviting huge investments from international brands especially in food and clothing sector. Changes in life style have made Saudi society more prone towards disease like diabetes that is costing about 40% cases of the total population [1]. Higher diabetic cases have alarmed health care organizations (both government and private) in finding the exact number of diabetic cases in extremely timely manner. Creating a unified system among hospitals, laboratories and other health care organizations is time consuming and expensive inviting researchers to look for other options. Due to improvement in community awareness among stakeholders (patients, care taker, health researcher and others), has provided an opportunity to get a real time estimate about total number of patients and getting to know about patient problems etc. This study tends to create a diabetic prediction system that will gather information from multiple sources (news, health care records, social media, news feeds, search trends and tweets) in multiple languages (Arabic , English and French) to answer two questions (1) Can online search trends and tweets be related to exact number of diabetes patients (2) Can we extract common or new symptoms for diabetes cases from these trends (3) providing a predictive picture to health care professionals and managers for creating in-time policies to avoid epidemic.(4) Finding relationship in between diabetes related search terms and diabetic cases. This study reveals that real data figures are 85% correlated to search trend thus providing a cogent proof that both internet usage and real data figures can be related. It was also observed that search trends commonly symbolize common symptoms or disease name. A cyber diabetic community can be created that can be targeted by government agencies or health organization as to create awareness about diabetes. While usage of system by community will also help in better diagnosis from search trends and hospital information.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-146-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/racs-15.2016.30How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yasir Javed
AU  - Adnan Khan
AU  - Basit Qureshi
AU  - Junaid Chaudhry
PY  - 2015/11
DA  - 2015/11
TI  - Estimating Diabetic cases in KSA through search trends and Creating Cyber Diabetic Community.
PB  - Atlantis Press
SP  - 173
EP  - 178
SN  - 2352-538X
UR  - https://doi.org/10.2991/racs-15.2016.30
DO  - https://doi.org/10.2991/racs-15.2016.30
ID  - Javed2015/11
ER  -