Doctors typically write in incomprehensible handwriting, making it difficult for both the general public and some pharmacists to understand the medications they have prescribed. It is not ideal for them to write the prescription quietly and methodically because they will be dealing with dozens of patients every day and will be swamped with work.As a result, their handwriting is illegible. This may result in reports or prescriptions consisting of short forms and cursive writing that a typical person or pharmacist won't be able to read properly, which will cause prescribed medications to be misspelled. However, some individuals are accustomed to writing prescriptions in regional languages because we all live in an area with a diversity of regional languages. It makes analyzing the content much more challenging. So, in this project, we'll use a recognition system to build a tool that can translate the handwriting of physicians in any language. This system will be made into an application which is fully autonomous in functioning. As the user uploads the prescription image the program will pre-process the image by performing image pre-processing, and word segmentations initially before processing the image for training. And it will be done for every language we require the model to detect. And as of the deduction model will be made using deep learning techniques including CNN, RNN, and LSTM, which are utilized to train the model. To match words from various languages that will be written in the system, Unicode will be used. Furthermore, fuzzy search and market basket analysis are employed to offer an end result that will be optimized from the pharmaceutical database and displayed to the user as a structured output.
翻译:医生们通常会用无法理解的笔迹写字, 使得公众和一些药剂师都很难理解他们开的药方。 对他们来说, 写处方很不理想, 因为他们会每天与数十名病人打交道, 并且会忙碌起来。 结果, 他们的笔迹是难以辨认的。 这可能会导致报告或处方, 包括短表格和咒语写法, 一个典型的人或药剂师无法正确阅读, 这会造成处方药被拼错。 但是, 一些人习惯用区域语言写处方, 因为我们都生活在一个区域语言多样化的地区。 这样做并不理想, 因为他们会安静和有条理地写处方处方处方处方处方。 因此, 在这个项目中, 我们将使用一个识别系统来构建一个工具, 可以翻译任何语言的医生笔迹。 这个系统将完全独立运作。 由于用户上传处方图像, 程序将提前处理图像, 并且会先用文字分割处方处方的处方处方处方处方处方, 因为我们生活在一个区域语言的多样性区域语言区域语言中, 将使用一个模型, 将展示一个模型, 将展示一个模型, 将显示一个模型。