Unscrambling disease progression at scale: fast inference of event permutations with optimal transport

Nov-19-2025, 17:08:13 GMT–Neural Information Processing Systems

Disease progression models infer group-level temporal trajectories of change in patients' features as a chronic degenerative condition plays out.

artificial intelligence, bayesian inference, machine learning, (17 more...)

Neural Information Processing Systems

Nov-19-2025, 17:08:13 GMT

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Country:
- Europe > United Kingdom (0.14)

Genre:
- Research Report
  - Experimental Study (1.00)
  - New Finding (0.93)

Industry:
- Health & Medicine
  - Diagnostic Medicine (0.93)
  - Therapeutic Area > Neurology
    - Alzheimer's Disease (0.71)

Technology:
- Information Technology
  - Artificial Intelligence
    - Machine Learning
      - Learning Graphical Models
        Directed Networks > Bayesian Learning (0.93)
        Undirected Networks > Markov Models (0.93)
      - Neural Networks (0.93)
      - Statistical Learning (0.93)
    - Representation & Reasoning > Uncertainty
      - Bayesian Inference (0.93)
  - Data Science (1.00)

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Unscrambling disease progression at scale: fast inference of event permutations with optimal transport

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