Systems and Methods for the Prediction of Post-Operative Cognitive Decline Using Blood-Based Inflammatory Biomarkers
AssigneesThe Board of Trustees of the Leland Stanford Junior University, Assistance Publique-Hopitaux de Paris, Institut Pasteur
InventorsBrice Gaudillière, Julien Hédou, Franck Verdonk
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Abstract
Embodiments herein describe systems and methods to generate a risk score for an individual to develop postoperative neurocognitive disorder (POND). Various embodiments obtain multi-omics data from an individual, such as genomics, transcriptomics, and proteomics. In certain embodiments, a machine learning algorithm is used to generate the risk score based on the multi-omics data. In further embodiments, clinical data is further used in the determination of the risk score.
Claims75
A method for determining risk for postoperative neurocognitive disorder (POND) for an individual following surgery, comprising:
- obtaining values of a plurality of features, wherein the plurality of features comprise a plurality of biological and clinical features from a plurality of omics;
- computing a risk score for POND for the individual based on the plurality of features using a model obtained via a machine learning technique;
- and
- providing an assessment of the individual's risk for developing POND based on the computed risk score.
Dependencies are inferred from the claim text.