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001     341387
005     20230827173312.0
024 7 _ |a G:(EU-Grant)101080288
|d 101080288
|2 CORDIS
024 7 _ |a G:(EU-Call)HORIZON-HLTH-2022-TOOL-12-two-stage
|d HORIZON-HLTH-2022-TOOL-12-two-stage
|2 CORDIS
024 7 _ |a corda_____he::101080288
|2 originalID
035 _ _ |a G:(EU-Grant)101080288
150 _ _ |a PERSONALIZED REHABILITATION VIA NOVEL AI PATIENT STRATIFICATION STRATEGIES
|y 2023-06-01 - 2027-05-31
372 _ _ |a HORIZON-HLTH-2022-TOOL-12-two-stage
|s 2023-06-01
|t 2027-05-31
450 _ _ |a PREPARE
|w d
|y 2023-06-01 - 2027-05-31
510 1 _ |0 I:(DE-588b)5098525-5
|a European Union
|2 CORDIS
680 _ _ |a PREPARE aims at advancing rehabilitation care for patients with chronic non-communicable diseases. As rehabilitation is a complex, multifaceted, and highly personal process, we currently lack reliable patient stratification and outcome prediction tools. While big data approaches provide a path forward, existing data sets pose numerous challenges. These challenges can be overcome by combining advances in clinical research, socio-behavioral and public health research, data science, and advanced statistical and AI learning methods. We will apply machine learning techniques on our large-scale patient data sets including key sociodemographic, living conditions, and behavioral information to stratify patients based on expected outcomes. A subsequent analysis will consider all potential predictors for rehabilitation outcome. Baseline strata and modifiers will be used to develop a comprehensive model of each clinical situation to increase management quality, improve outcomes, and reduce costs. As proof of principle we will develop a platform for sharing model results, exploiting the open-science EHDEN platform, and showcase the novel approach through pilot cases of nine pathologies which constitute the most dominant causes for rehabilitation worldwide: hand disorders, hip and knee prosthesis, intermittent claudication, lower limb loss, Parkinson’s disease/Parkinsonisms, scoliosis, spine disorders, temporo-mandibular articulation, and hypertension. We will also develop a certification roadmap. PREPARE will result in innovative, robust, personalized, and validated data-driven computational prediction and stratification tools to support healthcare professionals and patients in selecting the optimal therapy strategy.
909 C O |o oai:juser.fz-juelich.de:1010746
|p authority:GRANT
|p authority
909 C O |o oai:juser.fz-juelich.de:1010746
980 _ _ |a G
980 _ _ |a CORDIS
980 _ _ |a AUTHORITY

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Marc 21