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DFSel-FT: A Differentiable Feature Selection and FT-Transformer Framework for Interpretable Thyroid Disease Classification Using Tabular Data

Thyroid diseases are very common endocrine diseases that afflict millions of people around the world and need proper and timely diagnosis to ensure proper treatment. Although machine learning and hybrid metaheuristic methods have advanced, current models have high computation costs, low interpretabi...

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Principais autores: Ganga Sagar Soni, Abhinav Shukla, R Kanesaraj Ramasamy, Pritendra Kumar Malakar, Parul Dubey
פורמט: Artigo
שפה:Inglês
יצא לאור: MDPI AG 2026-05-01
סדרה:Computers
נושאים:
thyroid disease diagnosis
transformer models
explainable AI
tabular data
feature gating
probability calibration
גישה מקוונת:https://www.mdpi.com/2073-431X/15/6/332
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