Abstract: Disclosed are techniques for using artificial intelligence (AI) to facilitate the treatment of subjects diagnosed with spinal muscular atrophy (SMA). Methods and systems disclosed herein relate to techniques for using AI to predict the disease progression in subjects diagnosed with SMA, detect latent commonalities across subjects with SMA to identify candidate subjects for new or existing clinical studies, and intelligently select subject-specific therapeutic treatments for treating SMA.

Abstract: 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.

Abstract: Disclosed are systems and methods for building and using a data platform to facilitate intelligent selection of treatments for multiple sclerosis and to identify indications for multiple-sclerosis treatments. Various record snapshots of records associated with multiple sclerosis subjects facilitate efficient queries that can be used to explore heterogeneous, unstructured and non-categorical data sets to generate concrete general hypotheses and subject-specific treatment predictions.

Abstract: Disclosed herein are systems, methods, and techniques for building and using a data platform to facilitate intelligent identification of coronavirus disease 2019 (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.

Abstract: 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.