Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) are two neurodegenerative diseases that cause progressive or alternating neurological impairments in motor, sensory, visual, and cognitive functions. Patients affected by these diseases undergo the physical, psychological, and economic burdens of hospital stays and home care while facing uncertainty. A possible aid to patients and clinicians might come from AI tools that can preemptively identify the need for intervention and suggest personalized therapies during the progression of these diseases. The objective of iDPP@CLEF is to develop automatic approaches based on AI that can be used to describe the progression of these two neurodegenerative diseases, with the final goal of allowing patient stratification as well as the prediction of the disease progression, to help clinicians in assisting patients in the most timely manner. iDPP@CLEF 2024 follows the two prior editions, iDPP@CLEF 2022 and 2023. iDPP@CLEF 2022 focused on ALS progression prediction and approaches of explainable AI for the task. iDPP@CLEF 2023 built upon iDPP@CLEF 2022 by extending the datasets provided during the previous edition with environmental data. Additionally, the 2023 edition of iDPP@CLEF introduced a new task focused on the progression prediction of MS. In this edition, we extended the MS dataset of iDPP@CLEF 2023 with environmental data. Furthermore, we introduced two new ALS tasks, focused on predicting the progression of the disease using data obtained from wearable devices, making it the first iDPP edition that uses prospective data collected directly from the patients involved in the BRAINTEASER project.
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2024
Bosoni, Pietro;Bergamaschi, Roberto;Dagliati, Arianna;Tavazzi, Eleonora;Vettoretti, Martina;
2024-01-01
Abstract
Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) are two neurodegenerative diseases that cause progressive or alternating neurological impairments in motor, sensory, visual, and cognitive functions. Patients affected by these diseases undergo the physical, psychological, and economic burdens of hospital stays and home care while facing uncertainty. A possible aid to patients and clinicians might come from AI tools that can preemptively identify the need for intervention and suggest personalized therapies during the progression of these diseases. The objective of iDPP@CLEF is to develop automatic approaches based on AI that can be used to describe the progression of these two neurodegenerative diseases, with the final goal of allowing patient stratification as well as the prediction of the disease progression, to help clinicians in assisting patients in the most timely manner. iDPP@CLEF 2024 follows the two prior editions, iDPP@CLEF 2022 and 2023. iDPP@CLEF 2022 focused on ALS progression prediction and approaches of explainable AI for the task. iDPP@CLEF 2023 built upon iDPP@CLEF 2022 by extending the datasets provided during the previous edition with environmental data. Additionally, the 2023 edition of iDPP@CLEF introduced a new task focused on the progression prediction of MS. In this edition, we extended the MS dataset of iDPP@CLEF 2023 with environmental data. Furthermore, we introduced two new ALS tasks, focused on predicting the progression of the disease using data obtained from wearable devices, making it the first iDPP edition that uses prospective data collected directly from the patients involved in the BRAINTEASER project.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.