Using machine reading to understand Alzheimer’s and related diseases from the literature

Abstract

Purpose: This paper aims to better understand a large number of papers in the medical domain of Alzheimer’s disease (AD) and related diseases using the machine reading approach. Design/methodology/approach: The study uses the topic modeling method to obtain an overview of the field, and employs open information extraction to further comprehend the field at a specific fact level. Findings: Several topics within the AD research field are identified, such as the Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS), which can help answer the question of how AIDS/HIV and AD are very different yet related diseases. Research limitations: Some manual data cleaning could improve the study, such as removing incorrect facts found by open information extraction. Practical implications: This study uses the literature to answer specific questions on a scientific domain, which can help domain experts find interesting and meaningful relations among entities in a similar manner, such as to discover relations between AD and AIDS/HIV. Originality/value: Both the overview and specific information from the literature are obtained using two distinct methods in a complementary manner. This combination is novel because previous work has only focused on one of them, and thus provides a better way to understand an important scientific field using data-driven methods.