The Recognition of Doctor's Handwritten Prescriptions: A Linguistic and Societal Perspective on Healthcare Communication

This research aims at creating a machine learning model as a solution which effectively transform's handwritten prescriptions into digital text with the help of Convolution Neural Networks (CNNs). As it is known that the challenges arised by having unreadable handwriting in medical prescriptions can lead to dangerous errors, to overcome these problems, the proposed system was derived ensuring the accurate identification of medications. The proposed system is trained on a wide set of handwritten samples, having achieved a high level of accuracy which remarkably improves the readability of the prescription. The proposed system reduces the possible mistakes while interpreting the handwritten prescription, minimizes the workload on pharmacists, leading to a better patient safety and providing healthcare professionals with an efficient tool.