A FRAMEWORK FOR DEDUCTIVE DATABASE DESIGN IM DECISION SUPPORT SYSTEMS

A three-level framework for design and implementation of deductive database management systems is described. The three levels consist of the abstraction, for abstracting the real world semantics, the language, for man-machine communication, and the environment, for specifying the hardware/software environment. This framework is applied to some representative systems. Based on the results, an architecture for a deductive database management system is proposed

Clinical Decision Support System for Unani Medicine Practitioners

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.Comment: 59 pages, 11 figures, Computer Science Bachelor's Thesis on use of Artificial Intelligence in Clinical Decision Support System for Unani Medicine

A Novel Approach Towards Automatic Text Summarization Using Lexical Chains

Text summarization is a process of extracting text by virtue of reduction of document contents while preserving the salient information intact. By using different set of parameters like position, format and type of sentences in an input text, frequency of words in a text etc., techniques have been developed. But the parameters vary depending on source of input texts. This in turn affects the performance of the algorithms. In this paper, we present a new method of automatic text summarization by making use of lexical cohesion in the text. Until now lexical chains have been used to model lexical cohesion. These lexical chains are sequences of words having semantic relations between them. In our proposed algorithm, we have used a modification of lexical chains to model the relationships that exist between words. DOI: 10.17762/ijritcc2321-8169.15081

An information management and analysis system for Illiac I

Includes bibliographic references (p. 20)

Design of a Bibliographic Data Base System

This report presents a definition of a data base and describes the major concepts considered in the design of a data base system. Demonstrating these concepts is an implemented data base system involving bibliographic data pertaining to computer science topics.Computing and Information Science