Authors
AUTHOR 1: ESRAA HASSAN,
AUTHOR 2: SHAZA BAHNACY
AUTHOR 3: HABIBA TAREK
AUTHOR 4: MAI HAZEM
SUPERVISED BY: DR. WALAA HASSAN EL-ASHMAWIE AND ENG. LOBNA SHAHEEN.
Publishing Date
26TH OCTOBER 2020
Abstract
At least 1.5 million people each year are being killed or furtherly sickened due to reading the medical prescription incorrectly in accordance with the National Academy of Sciences. This proposed system presents a solution to this issue through a software application that recognizes handwritten medicine names in English language and returns a readable digital text. This will help in diminishing the instances of distortion of medication names and will assist drug specialists with limiting their doubts when selling to the patient , the medicine. The proposed system shall be able to scan the prescription, recognize it then return in the form of a digital text and checks the availability of the medicine as it will be connected to the pharmacy’s system.
1.1 Purpose
The main purpose of this document is to outline the description of the medical prescription recognition system. The system aims to read medical prescriptions and return a readable digital text for the prescribed medicines. Furthermore, the document will present the details of the system’s functions and features. Not only does this document show an explicit user interface and how the system will deal with the user interactions
1.2 Scope
Medical prescriptions should be scanned by a camera phone with high camera resolution, photos should be taken from an appropriate and zoomed in angle, to ensure that the scanned image is clear and it’s content is visible.
1.3 Overview
Throughout the following software design description document, we will shed a spotlight on the architectural design used to develop our system and its pros and cons. Moreover, we will focus on the used design patterns and the structural viewpoints. Not only is talking about the Data designs and descriptions mandatory but also, without the diagrams such as the class diagram, sequence diagram, context model, etc.
1.4 Intended audience
The intended audiences for this project are mainly the pharmacists and any general user who finds it hard to read the doctors’ illegible handwriting off the medical prescription. Concerning the accuracy and the precision of the system Pharmacist will be able to train the system and enter the correct medicine name, if the prescribed medicine was not detected at all. And the pharmacist will be able to edit the medicine name if the prescribed medicine was detected incorrectly. Therefore, Pharmacists will be admitted to the application by their national ids and faculty ids and an approval from the admin to ensure efficacy and security.