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FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial
Research article (PLoS ONE, 2024) · cited 12× · AI/ML
FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial
Summary
FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial is a scholarly article[1].
Key Facts
FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial's Study protocol of a multicenter trial — 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). FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial. Retrieved May 24, 2026, from https://4ort.xyz/entity/female-the-use-of-machine-learning-for-early-diagnosis-of-endometriosis-based-on-patient-self-reported-datastudy-protoco
MLA“FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/female-the-use-of-machine-learning-for-early-diagnosis-of-endometriosis-based-on-patient-self-reported-datastudy-protoco.
BibTeX@misc{4ortxyz_female-the-use-of-machine-learning-for-early-diagnosis-of-endometriosis-based-on-patient-self-reported-datastudy-protoco_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial}}, year = {2026}, url = {https://4ort.xyz/entity/female-the-use-of-machine-learning-for-early-diagnosis-of-endometriosis-based-on-patient-self-reported-datastudy-protoco}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data—Study protocol of a multicenter trial — https://4ort.xyz/entity/female-the-use-of-machine-learning-for-early-diagnosis-of-endometriosis-based-on-patient-self-reported-datastudy-protoco (retrieved 2026-05-24)
