iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients
Summary
iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients is a scholarly article[1].
Key Facts
iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients'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). iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients. Retrieved May 24, 2026, from https://4ort.xyz/entity/icovid-interpretable-deep-learning-framework-for-early-recovery-time-prediction-of-covid-19-patients
MLA“iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/icovid-interpretable-deep-learning-framework-for-early-recovery-time-prediction-of-covid-19-patients.
BibTeX@misc{4ortxyz_icovid-interpretable-deep-learning-framework-for-early-recovery-time-prediction-of-covid-19-patients_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients}}, year = {2026}, url = {https://4ort.xyz/entity/icovid-interpretable-deep-learning-framework-for-early-recovery-time-prediction-of-covid-19-patients}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): iCOVID: interpretable deep learning framework for early recovery-time prediction of COVID-19 patients — https://4ort.xyz/entity/icovid-interpretable-deep-learning-framework-for-early-recovery-time-prediction-of-covid-19-patients (retrieved 2026-05-24)
