Combining AI approaches for the diagnosis and prognosis of neurodegenerative diseases

Jeanette Hellgren Kotaleski

doi:10.1117/12.2594550

2 August 2021 Combining AI approaches for the diagnosis and prognosis of neurodegenerative diseases

Jeanette Hellgren Kotaleski

Proceedings Volume 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021; 118040V (2021) https://doi.org/10.1117/12.2594550
Event: SPIE Nanoscience + Engineering, 2021, San Diego, California, United States

Abstract

This abstract is part of the symposium: "Diagnosis and Prediction of Neurodegenerative Diseases using Artificial Intelligence and Simulations". In this talk the different approaches discussed during the symposium will be summarized. In brief, information and communication technology (ICT) approaches are an important tool to manage, analyze and integrate the data derived from the brains of patients with neurodegenerative diseases. However, the challenge that these approaches now face is to integrate all the multi-scale changes in brain structure and dynamics that occur in these diseases, from alterations at the molecular level to changes in large-scale brain networks. Another important challenge that ICT approaches must solve is to determine the changes that play a causal role in these diseases, are compensatory, or simply correlated to the disease condition. I will provide an overview of this integrative multi-scale approach and show concrete examples that highlight its feasibility.

Conference Presentation

Citation Download Citation

Jeanette Hellgren Kotaleski "Combining AI approaches for the diagnosis and prognosis of neurodegenerative diseases", Proc. SPIE 11804, Emerging Topics in Artificial Intelligence (ETAI) 2021, 118040V (2 August 2021); https://doi.org/10.1117/12.2594550

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