A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization

<b>Background:</b> Lumbar disc herniation (LDH) recurrence remains a pressing clinical challenge, with limited predictive tools available to support early identification and personalized intervention. Predicting recurrence after lumbar disc herniation (LDH) remains clinically important but algorithm...

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Príomhchruthaitheoirí:	Mădălina Duceac (Covrig), Călin Gheorghe Buzea, Alina Pleșea-Condratovici, Lucian Eva, Letiția Doina Duceac, Marius Gabriel Dabija, Bogdan Costăchescu, Eva Maria Elkan, Cristian Guțu, Doina Carina Voinescu
Formáid:	Artigo
Teanga:	Inglês
Foilsithe / Cruthaithe:	MDPI AG 2025-06-01
Sraith:	Diagnostics
Ábhair:	lumbar disc herniation recurrence prediction ensemble learning autoencoder threshold tuning class imbalance
Rochtain ar líne:	https://www.mdpi.com/2075-4418/15/13/1628
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A Hybrid Ensemble Learning Framework for Predicting Lumbar Disc Herniation Recurrence: Integrating Supervised Models, Anomaly Detection, and Threshold Optimization

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