According to the World Health Organization, 15 million people suffer stroke worldwide each year. This project (DocStroke) aims to provide the cheap technique to determine the risks of stroke using ocular image processing and machine learning that any rural medical institution could afford, so they could warn the stroke and prevent it from happening with all of its side effects, including deaths caused by the stroke. The background research shows that modifiable factors are strongly correlated with the risks of developing stroke and we can deduce these factors from the ocular fundus image. Also, the portable Panoptic ophthalmoscope can take images of the eye fundus with 5x times larger view even if the pupil is not dilated. “DocStroke” is the application that calculates these risks. The calculation is based on the eye fundus image taken from the patient through the ophthalmoscope and the information provided in questioner, both of them are analyzed by the DocStroke application which provides the accurate and cheap way of determination of risks of stroke.
Our team consists of two members:
1- Zena Gharib: Programmer, scientific and market researcher.
2- Mohammad Rimawi: Designer, responsible for social media.
Technologies we are looking to use in our projects
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