Developing Concept Enriched Models for Big Data Processing Within the Medical Domain

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Akhil Gudivada (Creator)

James Philips (Creator)

Nasseh Tabrizi (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Within the past few years, the medical domain has endeavored to incorporate artificial intelligence, including cognitive computing tools, to develop enriched models for processing and synthesizing knowledge from Big Data. Due to the rapid growth in published medical research, the ability of medical practitioners to keep up with research developments has become a persistent challenge. Despite this challenge, using data-driven artificial intelligence to process large amounts of data can overcome this difficulty. This research summarizes cognitive computing methodologies and applications utilized in the medical domain. Likewise, this research describes the development process for a novel, concept-enriched model using the IBM Watson service and a publicly available diabetes dataset and knowledge-base. Finally, reflection is offered on the strengths and limitations of the model and enhancements for future experiments. This work thus provides an initial framework for those interested in effectively developing, maintaining, and using cognitive models to enhance the quality of healthcare.

Additional Information

Publication

Other

Gudivada, Akhil,et al. "Developing Concept Enriched Models for Big Data Processing Within the Medical Domain." IJSSCI 12.3 (2020): 55-71. Web. 24 Mar. 2021. doi:10.4018/IJSSCI.2020070105

Language: English

Date: 2023

Subjects

Artificial Intelligence;Cognitive Computing;Big Data;Medical;Information Retrieval

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