Hoffmann-la Roche Inc.

F. Hoffmann-la Roche Ag

Turap Tasoglu

Silvia Elena Molero Leon

Hélène Jeanne Sahri

Disclosed herein are systems, methods, and techniques for building and using a data platform to facilitate intelligent identification of coronavirus disease(COVID-19) related diagnoses, treatment selection, and interaction tracing. The present disclosure relates to a cloud-based application that generates outputs predictive of a subject's COVID-19 diagnoses and/or suitability for COVID-19 treatments.

Intelligent workflow analysis for treating covid-19 using exposable cloud-based registries

Disclosed are systems and methods for building and using a machine-learning model to facilitate intelligent selection of treatment strategies for subjects suffering from hemophilia. Sensor data (e.g., that characterizes movement of or a physiological characteristic of particular a subject) can be used as an input to a machine-learning model workflow. The sensor data may affect a model selection, model configuration, model result, pre-processing and/or post-processing. A result of the workflow may inform or influence a treatment selection, treatment schedule, treatment dosage and/or activity recommendation for the particular subject.

Machine-learning model for generating hemophilia pertinent predictions using sensor data

Disclosed are systems and methods for building and using a data platform to perform intelligent treatment selection to assist in clinical decision making. The present disclosure relates to a server configured to transform a subject record, which characterizes various non-numerical features of a subject, into a transformed representation that is consumable by machine-learning or artificial intelligence models. The output of the machine-learning or artificial-intelligence models can be evaluated to enable the intelligent treatment selection and other enhanced analyses, such as, for example, automatically detecting and defining subject populations, predicting treatment protocols with likely positive responsiveness, and identifying the similarity or dissimilarity between subject records along one or more dimensions.

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Basel, Switzerland

Turap Tasoglu