ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder.

Area of Science:

• Medical Informatics
• Neuroscience
• Data Science

Background:

• Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent condition impacting behavior, daily functioning, and relationships.
• Information on ADHD, including medications and clinical data, is fragmented across numerous online sources.
• Existing general-purpose knowledge graphs lack the specificity required for in-depth ADHD research.

Purpose of the Study:

• To develop a domain-specific Knowledge Graph of ADHD (KGA) for enhanced data integration and retrieval.
• To focus on adult ADHD, consolidating information from literature, clinical trials, and medication data.
• To address the challenges of manual data aggregation faced by researchers and clinicians.

Main Methods:

• An automated procedure was developed to construct the KGA.
• Data integration involved linking diverse sources like literature, clinical trials, and medication side-effect information.
• Information linking utilized common concepts from medical thesauri for resource connection.

Main Results:

• A comprehensive Knowledge Graph of ADHD was successfully constructed.
• Use cases demonstrated the KGA's effectiveness in enhancing and accelerating information retrieval.
• The KGA facilitates more efficient exploration of ADHD-related knowledge.

Conclusions:

• The Knowledge Graph of ADHD offers significant value to researchers and clinicians.
• It supports various processes including ADHD research, training, diagnosis, and treatment.
• The KGA streamlines access to critical information for improved patient care and scientific advancement.