Abstract for Medical prescription text OCR using Google OCR
A Doctor’s prescription is a handwritten document written by doctors in the form of instructions that describes list of drugs for patients in time sickness, injuries and other disability problems.
While we receiving a new prescription from doctor, it is unable to understand what drug name is prescribed on it.
In most cases, however, we wouldn’t be able to read it anyway because doctors use Latin abbreviations and medical terminologies on prescriptions that are not understandable by the general persons which make reading it very difficult. Peoples are sickened, injured or killed each year by errors while reading prescription.
This paper resolves the problems in doctor’s prescriptions by using OCR (Handwritten) based on median details what are all the components are used along with that cost if cost is more, we can recommend some other median.
Introduction to Google OCR based Medical Prescription
The medical laboratory report is one kind of important clinical data, which helps health care professionals with patient assessment, diagnosis, and long-term monitoring. The digitization process of healthcare services has been introduced into European countries under study during the last ten years.
It has already reached excellent levels in some countries, especially in Northern Europe. In North America, the US government has also granted the substantial federal financial incentives to promote the adoption and use of electronic health records (EHRs).
However, the situation may be different in developing countries, where paper documents are still common for health reports and records in hospitals.
Based on the above background, the purpose of our work is making papery medical laboratory reports digitalized for EHR system, which mainly relates to optical character recognition (OCR) techniques, especially text detection and recognition.
Though OCR is well-established for certain applications, text detection and recognition still face many challenges, such as the diversified requirements in different scenes (e.g., texts in street scene for robot navigation and receipts OCR for financial departments) and lower quality or degraded data (e.g., scanned legacy books in Google Books service).
This work focuses on the digitization of documents in the medical scene. The most significant challenge to apply a text detection model to a documental image is that the image usually has a high resolution and many textual objects, while the single textual object occupies a very small region. Know About Medical prescription text OCR using Google OCR below.
System Architecture Of Medical prescription text OCR using Google OCR
H/w and S/W requirements
Computer : System.
Ram : 1GB
Rom : 32GB
Technology : Machine Learning.
Front End : GUI-tkinter.
IDLE : python 3.10.4
Virtual Envs : Anaconda