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Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
Research article (2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2016) · cited 74× · AI/ML
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
Summary
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT is a scholarly article[1].
Key Facts
Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT's instance of is recorded as scholarly article[2].
References
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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.
APA4ort.xyz Knowledge Graph. (2026). Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT. Retrieved May 24, 2026, from https://4ort.xyz/entity/combining-deep-neural-network-and-traditional-image-features-to-improve-survival-prediction-accuracy-for-lung-cancer-pat
MLA“Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/combining-deep-neural-network-and-traditional-image-features-to-improve-survival-prediction-accuracy-for-lung-cancer-pat.
BibTeX@misc{4ortxyz_combining-deep-neural-network-and-traditional-image-features-to-improve-survival-prediction-accuracy-for-lung-cancer-pat_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT}}, year = {2026}, url = {https://4ort.xyz/entity/combining-deep-neural-network-and-traditional-image-features-to-improve-survival-prediction-accuracy-for-lung-cancer-pat}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT — https://4ort.xyz/entity/combining-deep-neural-network-and-traditional-image-features-to-improve-survival-prediction-accuracy-for-lung-cancer-pat (retrieved 2026-05-24)
