Home › Entities › academia › Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy

Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy

Research article (Computerized Medical Imaging and Graphics, 2021) · cited 14× · AI/ML
academia openalex:W3169054605
Press Enter · cited answer in seconds

Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy

Summary

Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy is a scholarly article[1].

Key Facts

  • Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy. Retrieved May 24, 2026, from https://4ort.xyz/entity/prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear
MLA “Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear.
BibTeX @misc{4ortxyz_prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy}}, year = {2026}, url = {https://4ort.xyz/entity/prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy — https://4ort.xyz/entity/prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/prediction-of-the-motion-of-chest-internal-points-using-a-recurrent-neural-network-trained-with-real-time-recurrent-lear · Last refreshed: