169 citations · 335 across the 56 of their papers we have counts for
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cs.LG2026
Transformer-Based Multi-Modal Temporal Embeddings for Explainable Metabolic Phenotyping in Type 1 Diabetes
Pir Bakhsh Khokhar, Carmine Gravino, Fabio Palomba +2
Type 1 diabetes (T1D) is a highly metabolically heterogeneous disease that cannot be adequately characterized by conventional biomarkers such as glycated hemoglobin (HbA1c). This s…
cs.LG2025★ 2 cited
Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence
Pir Bakhsh Khokhar, Viviana Pentangelo, Fabio Palomba +1
Diabetes mellitus (DM) is a global health issue of significance that must be diagnosed as early as possible and managed well. This study presents a framework for diabetes predictio…