COMMITMENT – Integrative Machine Transfer Learning for Psychiatric Diseases
The project "COMorbidity Modeling via Integrative Transfer machine-learning in MENTal illness" (COMMITMENT) will establish an interdisciplinary research framework for the identification of systems-molecular hallmarks of psychotic and comorbid somatic diseases. The identification of shared and distinct biological profiles and their underlying pathophysiological processes will allow disentangling patient heterogeneity and provide the basis for objective tools for personalized clinical management of psychotic disorders.
The overall aim of COMMITMENT is to develop a computational systems medicine framework that allows clinically meaningful stratification of psychotic disorders and the identification of biological processes shared with somatic and neurodegenerative comorbidities.
Fraunhofer SCAI is leading the subproject „TP3 – Systems medicine knowledge and mechanisms“. In this subproject, the knowledge available in the scientific literature in the field of psychotic diseases and their co-morbidities (diabetes; neurodegenerative diseases) will be systematically collected and presented in a form that can be used for machine learning procedures in further work packages of the project.
Project duration: 09/2019 – 08/2022