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Handwritten Prescription Analysis

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dc.contributor.author Wijesooriya, Anjali
dc.date.accessioned 2022-12-19T07:35:00Z
dc.date.available 2022-12-19T07:35:00Z
dc.date.issued 2022
dc.identifier.citation Wijesooriya, Anjali (2022) Handwritten Prescription Analysis. BEng. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2018028
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1170
dc.description.abstract "Doctors are issuing a prescription to patients, which have prescribed medicines for relevant illness/disease. Usually, these prescriptions are handwritten documents. In general, every person has a unique handwriting style. When it comes to doctors’ handwritings, the written content is mostly unidentifiable. Majority of them use cursive handwriting style to write. Therefore, the written content of the prescription is mostly incomprehensive. It requires a lot of training to understand what is written in cursive handwriting. Since it contains medical information, it needs to interpret properly. As a solution for above mentioned problem, from this research the author has proposed the solution to develop a system where the user can upload the image of the prescription and make it interpret. Therefore, the pharmacists can issue medicines according to the interpreted prescription. The system will be used a dataset extracted from prescriptions to train the machine learning model to convert the handwritten characters to digital text. " en_US
dc.language.iso en en_US
dc.subject Handwritten Character Recognition en_US
dc.subject Prescription en_US
dc.subject Machine learning en_US
dc.subject Image processing en_US
dc.title Handwritten Prescription Analysis en_US
dc.type Thesis en_US


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