Conversion of Legal Text to a Logical Rules Set from Medical Law Using the Medical Relational Model and the World Rule Model for a Medical Decision Support System

Journal Title: Informatics - Year 2016, Vol 3, Issue 1

Abstract

Automated formalization of legal text is a time- and effort-consuming task, but human-based validation consumes even more of both. The exchange of healthcare data in compliance with the medical privacy law requires experts with deep familiarity of its intricate provisions for verification. The article presents a medical relational model (MRM) for the extraction of logical rules from medical law, required to design a medical decision support system (MDSS) that facilitates the process of exchanging data electronically with minimum human intervention. The division of medical law into small concept classes makes it easier to formalize the legal text of medical law into logical rules. These logical rules are then used to make a precise decision in compliance with the law, after evaluating requests from different entities for different purposes in MDSS. Our methodology is to analyze the legal text and release records in compliance with the medical law. For developing countries where medical laws are not as mature as HIPAA (Health Insurance Portability and Accountability Act) in the USA, the proposed methodology can be adapted to build their MDSS based on MRM.

Authors and Affiliations

Imran Khan, Muhammad Sher, Javed I. Khan, Syed M. Saqlain, Anwar Ghani, Husnain A. Naqvi and Muhammad Usman Ashraf

Keywords

Related Articles

Improving Semantic Similarity with Cross-Lingual Resources: A Study in Bangla—A Low Resourced Language

Semantic similarity is a long-standing problem in natural language processing (NLP). It is a topic of great interest as its understanding can provide a look into how human beings comprehend meaning and make association...

Web Apps Come of Age for Molecular Sciences

Whereas server-side programs are essential to maintain databases and run data analysis pipelines and simulations, client-side web-based computing tools are also important as they allow users to access, visualize and an...

Evaluating Awareness and Perception of Botnet Activity within Consumer Internet-of-Things (IoT) Networks

The growth of the Internet of Things (IoT), and demand for low-cost, easy-to-deploy devices, has led to the production of swathes of insecure Internet-connected devices. Many can be exploited and leveraged to perform l...

A Comprehensive Study of Activity Recognition Using Accelerometers

This paper serves as a survey and empirical evaluation of the state-of-the-art in activity recognition methods using accelerometers. The paper is particularly focused on long-term activity recognition in real-world set...

Alt-Splice Gene Predictor Using Multitrack-Clique Analysis: Verification of Statistical Support for Modelling in Genomes of Multicellular Eukaryotes

One of the main limitations of the typical hidden Markov model (HMM) implementation for gene structure identification is that a single structure is identified on a given sequence of genomic data—i.e., identification of...

Download PDF file
  • EP ID EP44048
  • DOI https://doi.org/10.3390/informatics3010002
  • Views 259
  • Downloads 0

How To Cite

Imran Khan, Muhammad Sher, Javed I. Khan, Syed M. Saqlain, Anwar Ghani, Husnain A. Naqvi and Muhammad Usman Ashraf (2016). Conversion of Legal Text to a Logical Rules Set from Medical Law Using the Medical Relational Model and the World Rule Model for a Medical Decision Support System. Informatics, 3(1), -. https://europub.co.uk/articles/-A-44048