Artificial neural networks combined with surface-enhanced laser desorption/ionization mass spectra distinguish endometriosis from healthy population

article OA: bronze CC0 ⤵ 17 in-corpus citations
AI-generated summary by claude@2026-06, 2026-06-08

This study developed an artificial neural network model that successfully distinguished endometriosis patients from healthy individuals using surface-enhanced laser desorption/ionization mass spectrometry data.

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Condition tags

endometriosis

MeSH descriptors

Endometriosis Neural Networks, Computer Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Uterine Diseases Adult Biomarkers Biomarkers CA-125 Antigen CA-125 Antigen Endometriosis Endometriosis Female Health Humans Middle Aged Protein Array Analysis Sensitivity and Specificity Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Uterine Diseases Uterine Diseases

Citation neighborhood

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (10)

Cited by (17)

Source provenance

europepmc
last seen: 2026-06-13T06:22:48.782012+00:00
openalex
last seen: 2026-06-04T00:00:01.174412+00:00
pubmed
last seen: 2026-05-13T22:15:00.519696+00:00
License: CC0 · commercial use OK