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| dc.contributor.author | Hasan, Tanjil | |
| dc.contributor.author | Lipu, Shiblur Rahman | |
| dc.contributor.author | Atikur Rahman | |
| dc.contributor.author | Khan, Istiaqe Ahmed | |
| dc.date.accessioned | 2020-12-07T11:06:55Z | |
| dc.date.available | 2020-12-07T11:06:55Z | |
| dc.date.issued | 2020-12-05 | |
| dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5334 | |
| dc.description | One of the most widely studied topics today is brain stroke. Strokes are defined by the World Health Organization which is an acute, focal or diffuse, dysfunction of the brain, originating for vessels and lasting for a period longer than a day. Stroke is the third leading disease of death in the United States. According to the WHO (World Health Organization) There are 15 million people suffer stroke worldwide every year, in which 5 million people die every year and another 5 million peoples are permanently disabled. People are very apathetic about stroke but it is a dangerous disease that pushes people towards death. The man is having a brain stroke but he can’t catch that he has a stroke. It is happening to many people now and its treatment is expensive. Because of the high cost of stroke treatment, people often try to avoid it but stroke can lead to death. It is a matter of concern for us that the number of strokes is increasing in Bangladesh and all over the world. Currently there is a lot of work being done on brain stroke. Our software will make it easier for patients to diagnose stroke and doctors will be able to monitor patients more easily. We used a lot of images of the brain for brain stroke in this project and used a lot of pictures of what causes a brain stroke and from those pictures our software will be able to understand brain stroke. We hope our project will benefit people a lot more. | en_US |
| dc.description.abstract | Most of the people (87%) are affected by Ischemic stroke. To distinguish this hemorrhage, we got to do a lab test at therapeutic. But that's exceptionally costly for our country individuals. So, we choose to do something for them. After huge research, we developed a project which can detect this type of hemorrhage using deep learning neural network based algorithm. To do that we collected raw data (CT Scan Copy) from a number of hospital, we preprocessed it with a help of radiologist and finally trained our model to nail our goal which is detecting hemorrhage stroke. Right now, we have achieved 90 up percentage accuracy in total. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Daffodil International University | en_US |
| dc.subject | Medical Care | en_US |
| dc.title | Doctor Engine | en_US |
| dc.title.alternative | A Health Care Assistant | en_US |
| dc.type | Other | en_US |
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Project Report [2666]