Intelligent disease progression prediction: overview of iDPP@ CLEF 2022

A Guazzo, I Trescato, E Longato, E Hazizaj… - … Conference of the Cross …, 2022 - Springer
Abstract Amyotrophic Lateral Sclerosis (ALS) is a severe chronic disease characterized by
progressive or alternate impairment of neurological functions, characterized by high …

An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology

G Faggioli, L Menotti, S Marchesin, A Chió… - Journal of Biomedical …, 2024 - Springer
Automatic disease progression prediction models require large amounts of training data,
which are seldom available, especially when it comes to rare diseases. A possible solution …

[HTML][HTML] Develo** guidelines for functionally-grounded evaluation of explainable artificial intelligence using tabular data

M Velmurugan, C Ouyang, Y Xu, R Sindhgatta… - … Applications of Artificial …, 2025 - Elsevier
Abstract Explainable Artificial Intelligence (XAI) techniques are used to provide transparency
to complex, opaque predictive models. However, these techniques are often designed for …

[PDF][PDF] Predicting and Explaining Risk of Disease Worsening Using Temporal Features in Multiple Sclerosis.

TM Buonocore, P Bosoni, G Nicora… - CLEF (Working …, 2023 - ceur-ws.org
We present an evaluation study of the usage of two different post-hoc model agnostic XAI
methods, namely SHAP and AraucanaXAI, to provide insights about the most predictive …

[CITARE][C] The Brainteaser Ontology: Progression and Monitoring of Brain-Related Diseases