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AI Biotech/Diagnostics: Other Innovation

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Patent US9764136


Issued 2017-09-19

Clinical Decision Support System

Example apparatus and methods concern a next generation clinical decision support system (ngCDSS) for the management of neurological conditions (e.g., advanced Parkinson's disease (PD)). Conventional coupled adjustment of pharmacologic therapy and stimulation parameter settings is a time-consuming process that sometimes yields sub-optimal outcomes. Example ngCDSS use a machine learning trained function that relates deep brain stimulation (DBS) parameters, medication dosages, and patient-specific pre and post operative clinical data with actual treatment outcomes for a population of previously treated patients. Example ngCDSS incorporate image-based patient-specific computer models of the estimated stimulation volume of tissue stimulated by DBS in a multi-linear regression analysis to produce a predictor function that is highly correlated with actual outcomes. Example ngCDSS facilitate predicting the outcomes of a combined pharmacologic-DBS therapy, which in turn facilitate optimizing patient-specific treatment for improved benefits with minimal adverse effects.



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1 Independent Claim

  • 1. An apparatus for selecting treatment parameters for a patient, comprising: a first circuit that produces first electronic data that characterizes a neuroanatomical condition of the patient, where the characterization of the neuroanatomical condition is based, at least in part, on an electrode implanted in a brain of the patient; a second circuit that produces second electronic data that characterizes the patient based on patient symptom data and patient non-symptom data; a processor that computes a similarity metric for the patient based, at least in part, on the first electronic data and the second electronic data; a third circuit that identifies relevant data associated with a set of other patients and their therapeutic outcomes based on the similarity metric; a fourth circuit that produces third electronic data identifying a combination of treatment parameters for the patient based, at least in part, on the relevant data, where the combination of treatment parameters includes one or more stimulation parameters and one or more medication parameters; and a fifth circuit that provides a visualization, to a display, of the relevant data from which the fourth circuit selects the combination of treatment parameters.