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Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications paper by Yvon K. Awuklu
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Paper

Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications

by Yvon K. Awuklu arxiv/2604.21793
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38.3 Top 10%
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R: Recency 79
Q: Quality 60
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In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge. Our framework employs logical rules to capture existence and termination conditions for simple temporal events and to combine these into meta-events. In the medical domain, for example, disease episodes and therapies are inferred from timestamped clinical observations, such as diagnoses and drug administrations stored in patient records, and...

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Registry ID 2604.21793
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BibTeX 
@misc{arxiv_2604_21793,
  author = {Yvon K. Awuklu},
  title = {Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications Paper},
  year = {2026},
  howpublished = {\url{https://arxiv.org/abs/2604.21793}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
Yvon K. Awuklu. (2026). Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications [Paper]. Free2AITools. https://arxiv.org/abs/2604.21793

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Semantic (S) 50

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Authority (A) 0
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Recency (R) 79
Quality (Q) 60

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FNI V2.0 for Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications: Authority (A:0), Popularity (P:0), Recency (R:79), Quality (Q:60). Semantic (S) is a query-time baseline scored live at search.

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📝 Executive Summary

"In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge. Our framework employs logical rules to capture existence and termination conditions for simple temporal events and to combine these into meta-events. In the medical domain, for example, disease episodes and therapies are inferred from timestamped clinical observations, such as diagnoses and drug administrations stored in patient records, and..."

❝ Cite Node 

@article{Awuklu2026Inferring,
  title={Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications},
  author={Yvon K. Awuklu},
  journal={arXiv preprint arXiv:2604.21793},
  year={2026}
}

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Yvon K. Awuklu

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✅60QualityFNI pillar
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id
2604.21793
slug
2604.21793
source
arxiv
author
Yvon K. Awuklu
license
arXiv
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arxiv:cs.AI

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