@article{1dcfb3452523483e909c2560ec01ae38,
title = "ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder",
abstract = "Purpose: Attention Deficit Hyperactivity Disorder (ADHD) is a widespread condition that affects human behaviour and can interfere with daily activities and relationships. Medication or medical information about ADHD can be found in several data sources on the Web. Such distribution of knowledge raises notable obstacles since researchers and clinicians must manually combine various sources to deeply explore aspects of ADHD. Knowledge graphs have been widely used in medical applications due to their data integration capabilities, offering rich data stores of information built from heterogeneous sources; however, general purpose knowledge graphs cannot represent knowledge in sufficient detail, thus there is an increasing interest in domain-specific knowledge graphs.Methods: In this work we propose a Knowledge Graph of ADHD. In particular, we introduce an automated procedure enabling the construction of a knowledge graph that covers knowledge from a wide range of data sources primarily focusing on adult ADHD. These include relevant literature and clinical trials, prescribed medication and their known side-effects. Data integration between these data sources is accomplished by employing a suite of information linking procedures, which aim to connect resources by relating them to common concepts found in medical thesauri. Results: The usability and appropriateness of the developed knowledge graph is evaluated through a series of use cases that illustrate its ability to enhance and accelerate information retrieval. Conclusion: The Knowledge Graph of ADHD can provide valuable assistance to researchers and clinicians in the research, training, diagnostic and treatment processes for ADHD.",
keywords = "Attention Deficit Hyperactivity Disorder, Adult ADHD, Mental Health, Knowledge Graph, Information Linking",
author = "Emmanuel Papadakis and George Baryannis and Sotirios Batsakis and Marios Adamou and Zhisheng Huang and Grigoris Antoniou",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
month = dec,
day = "1",
doi = "10.1007/s13755-023-00253-8",
language = "English",
volume = "11",
journal = "Health Information Science and Systems",
issn = "2047-2501",
publisher = "Springer London",
number = "1",
}