CLAIApr 14, 2015

Temporal ordering of clinical events

arXiv:1504.03659v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses temporal ordering in clinical data, but it appears incremental as it builds on existing extraction and linking techniques.

The authors tackled the problem of anchoring clinical events onto a temporal space by extracting events, temporal expressions, and links, and validated these methods using high-quality datasets.

This report describes a minimalistic set of methods engineered to anchor clinical events onto a temporal space. Specifically, we describe methods to extract clinical events (e.g., Problems, Treatments and Tests), temporal expressions (i.e., time, date, duration, and frequency), and temporal links (e.g., Before, After, Overlap) between events and temporal entities. These methods are developed and validated using high quality datasets.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes