Digitization, Analysis & Prediction of Medical Reports Using Deep Learning

Digitization, Analysis & Prediction of Medical Reports Using Deep Learning

Rakesh Merugu1, Aryan Mantoo1, Aseem Manna1, Gaurav Meshram1

UG Students, Department of Information Technology, Dr. D. Y. Patil Institute of Engineering and Technology, Ambi, Pune, Maharashtra, India.1

Abstract — Advancements in Deep Learning have enabled the healthcare industry to efficiently process and analyze a vast amount of medical data, including critical information about patients' health. Medical reports, in particular, contain valuable data that can help identify trends, patterns, and anomalies in patients' medical conditions, leading to better diagnosis and treatment plans. In this paper, we present an approach that utilizes deep learning algorithms, specifically CNN to predict, digitize, and analyze medical reports. An approach is proposed that uses OCR technology to digitize the reports, making it easier to analyze and store them in a digital format. This approach has the potential to improve the accuracy, efficiency, and quality of medical diagnosis and treatment, and can address challenges such as doctor prescription digitization, brain tumor classification, kidney stone classification, and skin disease classification. The approach is implemented in an Android application built using React Native, which enables healthcare providers to access these services through their smartphones.

Keywords—Medical Reports, Medical Services, Medical Reports Analysis, Human Diseases, Deep Learning, Prescription Digitization