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AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer

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AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer

Summary

AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer is a scientific publication[1].

Key Facts

  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Sri Priya Ponnapalli[2].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Penelope Miron[3].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Kristy L. S. Miskimen[4].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Kristin A. Waite[5].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Nadiya Sosonkina[6].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer authored Sara E. Coppens[7].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's instance of is recorded as scientific publication[8].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's publisher is recorded as Association for Computing Machinery[9].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's publisher is recorded as Institute of Electrical and Electronics Engineers[10].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's page is recorded as 117-118[11].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's DOI is recorded as 10.1145/3624062.3624078[12].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's language of work or name is recorded as English[13].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's publication date is recorded as +2023-11-12T00:00:00Z[14].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's main subject is recorded as artificial intelligence[15].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's main subject is recorded as machine learning[16].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's main subject is recorded as multi-tensor decomposition[17].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's title is recorded as AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer[18].
  • AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's presented in is recorded as ACM/IEEE Supercomputing Conference[19].

Body

Designation and Status

AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer's instance of is recorded as scientific publication[8].

References

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

Direct Wikidata claims

  1. [8] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  2. [2] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  3. [3] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  4. [4] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  5. [5] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  6. [6] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  7. [7] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  11. [12] ↑ . Q5188229. Retrieved . api.crossref.org. Provenance: wikidata.org.
  12. [13] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  13. [14] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  14. [15] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  15. [16] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  16. [17] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  17. [18] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.
  18. [19] ↑ . sc23.conference-program.com. sc23.conference-program.com. Provenance: wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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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). AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer. Retrieved May 3, 2026, from https://4ort.xyz/entity/ai-ml-derived-whole-genome-predictor-prospectively-and-clinically-predicts-survival-and-response-to-treatment-in-brain-cancer
MLA “AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/ai-ml-derived-whole-genome-predictor-prospectively-and-clinically-predicts-survival-and-response-to-treatment-in-brain-cancer.
BibTeX @misc{4ortxyz_ai-ml-derived-whole-genome-predictor-prospectively-and-clinically-predicts-survival-and-response-to-treatment-in-brain-cancer_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer}}, year = {2026}, url = {https://4ort.xyz/entity/ai-ml-derived-whole-genome-predictor-prospectively-and-clinically-predicts-survival-and-response-to-treatment-in-brain-cancer}, note = {Accessed: 2026-05-03}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): AI/ML-derived whole-genome predictor prospectively and clinically predicts survival and response to treatment in brain cancer — https://4ort.xyz/entity/ai-ml-derived-whole-genome-predictor-prospectively-and-clinically-predicts-survival-and-response-to-treatment-in-brain-cancer (retrieved 2026-05-03)

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