TY - JOUR
T1 - ADHD-KG
T2 - a knowledge graph of attention deficit hyperactivity disorder
AU - Papadakis, Emmanuel
AU - Baryannis, George
AU - Batsakis, Sotirios
AU - Adamou, Marios
AU - Huang, Zhisheng
AU - Antoniou, Grigoris
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12/1
Y1 - 2023/12/1
N2 - 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.
AB - 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.
KW - Attention Deficit Hyperactivity Disorder
KW - Adult ADHD
KW - Mental Health
KW - Knowledge Graph
KW - Information Linking
UR - https://www.scopus.com/pages/publications/85176280787
U2 - 10.1007/s13755-023-00253-8
DO - 10.1007/s13755-023-00253-8
M3 - Article
SN - 2047-2501
VL - 11
JO - Health Information Science and Systems
JF - Health Information Science and Systems
IS - 1
M1 - 52
ER -