From spoken narratives to domain knowledge: Mining linguistic data for medical image understanding

From spoken narratives to domain knowledge: Mining linguistic data for medical image understanding

Highlights • The medical images that can be described more consensually by physicians tend to be less diagnostically challenging. • The medical images that can be described with highly related concepts by most physicians tend to be less diagnostically challenging. • We develop a method based on anch...

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Veröffentlicht in:Artificial intelligence in medicine 2014-10, Vol.62 (2), p.79-90
Hauptverfasser: Guo, Xuan, Yu, Qi, Alm, Cecilia Ovesdotter, Calvelli, Cara, Pelz, Jeff B, Shi, Pengcheng, Haake, Anne R
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Artificial intelligence
Biological and medical sciences
Clustering algorithm
Computer science
control theory
systems
Computerized medical documentation
Computerized, statistical medical data processing and models in biomedicine
Correlation analysis
Data Mining
Data processing. List processing. Character string processing
Diagnostic Imaging
Diagnostic systems
Exact sciences and technology
General aspects
Humans
Image-based diagnostic reasoning
Inspection
Internal Medicine
Lexical consensus
Linguistics
Medical
Medical data analysis
Medical sciences
Memory organisation. Data processing
Narratives
Occupational training. Personnel. Work management
Other
Pattern recognition. Digital image processing. Computational geometry
Physicians
Semantic relatedness
Software
Unified Medical Language System
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Zusammenfassung:Highlights • The medical images that can be described more consensually by physicians tend to be less diagnostically challenging. • The medical images that can be described with highly related concepts by most physicians tend to be less diagnostically challenging. • We develop a method based on anchor concepts to cluster diagnostic narratives by image.
ISSN:0933-3657
1873-2860
DOI:10.1016/j.artmed.2014.08.001