A Structural FHMM for Interpretable Disease Trajectories in T2DM

arXiv:2608.24328 · cs.LG · Submitted 2026-08-25 · Read on arXiv

cs.LG

Submitted: 2026-08-25

Updated: 2026-08-25

Terminology

• Clustering — 8× in this paper · explained in 2 episodes
• Latent Representation — 6× in this paper · explained in 2 episodes
• Cumulative Incidence Function — 5× in this paper
• Factorial Hidden Markov Model — 5× in this paper
• Aggregation — 4× in this paper · explained in 1 episode
• Interpretability — 4× in this paper · explained in 15 episodes
• Body Mass Index — 3× in this paper
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Objective Function — 3× in this paper · explained in 2 episodes
• Copula — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Longitudinal Data — 2× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Swiss Data Science Center — 2× in this paper
• Akaike Information Criterion — 1× in this paper
• Alignment — 1× in this paper · explained in 1 episode
• Bayesian Information Criterion — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes

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