Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge

Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) are chronic diseases that cause progressive or alternating neurological impairments in motor, sensory, visual, and cognitive functions. Affected patients must manage hospital stays and home care while facing uncertainty and significant psychological and economic burdens that also affect their caregivers. To ease these challenges, clinicians need automatic tools to support them in all phases of patient treatment, suggest personalized therapeutic paths, and preemptively indicate urgent interventions. iDPP@CLEF aims at developing an evaluation infrastructure for AI algorithms to describe ALS and MS mechanisms, stratify patients based on their phenotype, and predict disease progression in a probabilistic, time-dependent manner. iDPP@CLEF 2023 was organised into three tasks, two of which (Tasks 1 and 2) pertained to Multiple Sclerosis (MS), and one (Task 3) concerned the evaluation of the impact of environmental factors in the progression of Amyotrophic Lateral Sclerosis (ALS), and how to use environmental data at prediction time. 10 teams took part in the iDPP@CLEF 2023 Lab, submitting a total of 163 runs with multiple approaches to the disease progression prediction task, including Survival Random Forests and Coxnets.