Preliminary Medical Diagnosis Using Voice-Based Urdu Language Interface

Muhammad Sajid; Kamran Ahsan; Muhammad Khalid Shaikh

Authors

Muhammad Sajid Department of Computer Science, University of Balochistan, Quetta
Kamran Ahsan Department of Computer Science, Federal Urdu University for Arts, Science and Technology Karachi.
Muhammad Khalid Shaikh Department of Computer Science, Federal Urdu University for Arts, Science and Technology Karachi.

Keywords:

Diagnostic Tree, Knowledge Base, Medical Diagnosis System, Artificial Intelligence, Speech Recognition

Abstract

Expert knowledge is stored in the knowledge base through an externalizing process in the form of facts, procedures, heuristics, and rules. The knowledge base helps to refine the present knowledge and insert new knowledge without recompiling a program. Medical diagnosis is one of the first knowledge-based areas in which expert system principles are applied. Almost all knowledge-based medical diagnostic systems take input symptoms in the form of text and rely on the English language. This is a hindrance to illiterate and non-native English speakers of developing countries to utilize the system, and unfortunately, Pakistan is one of them. In this connection, this paper proposed an indexing method for integrating the medical diagnostic knowledge base with a Pakistani National Language-based voice-oriented user interface for accommodating the illiterate.

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