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From Data to Decision: Development and Open Multi-Center Validation of an AI-Enabled Decision Support System for Pediatric Epilepsy Diagnosis and Treatment

Research output: Contribution to journal › Article › peer-review

Abstract

Decision support systems (DSS) support clinical reasoning with evidence-based recommendations. In pediatric epileptology, integrating multimodal data-EEG, seizure semiology, therapy, imaging, etc.-can improve diagnostic consistency and guide therapy selection beyond EEG-only approaches. Advances in attention-based deep learning enable the detection of complex patterns in real-world data while preserving clinician oversight and alignment with ILAE standards. Our goal is to develop and validate an AI-enabled DSS that supports standardized diagnosis and treatment decision-making in children and adolescents with epilepsy, and to establish an open, scalable framework for multi-center external validation.
Original languageEnglish
JournalNeuropediatrics - Journal of Pediatric Neurobiology, Neurology and Neurogenetics
DOIs
Publication statusE-pub ahead of print - 27 Apr 2026

Fields of science

  • 302035 Paediatrics and adolescent medicine
  • 102022 Software development
  • 502050 Business informatics
  • 102040 Quantum computing 
  • 509026 Digitalisation research
  • 211928 Systems engineering
  • 102034 Cyber-physical systems
  • 502032 Quality management
  • 102020 Medical informatics
  • 102006 Computer supported cooperative work (CSCW)
  • 102027 Web engineering
  • 102016 IT security
  • 503015 Subject didactics of technical sciences
  • 102015 Information systems
  • 301405 Neuropathology
  • 302052 Neurology
  • 302051 Neurosurgery
  • 301114 Cell biology

JKU Focus areas

  • Digital Transformation

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