MediSmart

An NLP driven intelligent medical assistant

https://doi.org/10.53730/ijhs.v6nS3.8051

Authors

  • Chalumuru Suresh Assistant Professor, Department of CSE, VNRVJIET, Hyderabad
  • Ravikanth M. Assistant Professor, Department of CSE, VNRVJIET, Hyderabad
  • Saketh Reddy Regatte Student Department of CSE, VNRVJIET, Hyderabad
  • Sahithi Vesangi Student Department of CSE, VNRVJIET, Hyderabad

Keywords:

natural language processing, flask web application, cloud storage system-firebase, flutter based android application, voice prescription

Abstract

Health Care is one of the most primary aspects of one’s personal life, where it is once deteriorated can never be restored forever. In this pathetic situation the people face immense difficulty in managing their health-related reports, documents etc. Another emerging problem in the health life is despite providing all the necessary advice in the prescription, there are still many suggestions & recommendations given by the doctor are not documented. Therefore, we propose a solution which demolishes the burden of carrying files or reports all the time to visit a doctor. This paper aims in implementing the MediSmart- An intelligent Medical Assistant, a system that comprises all the patients’ history, consolidated report along with most important information suggested by the doctor orally is recorded (voice prescription). Since the approach is patient-centric we intend to implement the MediSmart Document Collection System, which collects patient personal information, hospital specific information, EHR and Voice records of doctor’s advice. Later, the EHRs are summarized, and a consolidated medical report is presented using NLP techniques and simultaneously, the voice record is also summarized to help patients keep a track of the oral prescription provided by the doctor. 

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Published

28-05-2022

How to Cite

Suresh, C., Ravikanth, M., Regatte, S. R., & Vesangi, S. (2022). MediSmart: An NLP driven intelligent medical assistant. International Journal of Health Sciences, 6(S3), 8593–8608. https://doi.org/10.53730/ijhs.v6nS3.8051

Issue

Section

Peer Review Articles