/medical-transcriptions

Automate the discovery of medical transcriptions

Primary LanguageJupyter NotebookMIT LicenseMIT

Project Overview

Overview

Background

  • Customer: Medical supporting staff
  • Goal: Organize medical transcriptions with right speciality category
  • Pains:: Manual organizing transcription is a hectic and time consuming process
  • Gains:: Speed up the process of organizing and can also help in searching medical transcriptions

Value Proposition

  • Product: The primary product is to categorize transscriptions into different medical speciality, the second version could be building a search mechanism to search customer medical transcription faster.
  • Alleviates: Automating categoization of transcriptions will reduce the efforts of medical staff for any discovery purpose
  • Advantages: There will be no manual reading process necessary to choose the right medical speciality for the medical staffs.

Objectives

  • Create an automated pipeline to organize medical transcription into it's correct speciality
  • Achieve > 85% for the classification problem
  • Build a search mechanism as a downstream feature on top of the classification to search medical transcriptions based on keywords

Solutions

  • Core Features
    • ML service to classify the incoming medical transcription
    • Feedback loop from the medical staff to identify incorrect classifications
    • Filter incorrect classifications with high confident score
  • Secondary Features
    • Build a search engine UI, to search transcriptions on demand
    • Integrate speciality classification ML service with search engine to reduce the search space
  • Constraints
    • Maintain low latency
    • Identify duplication of medical transcriptions