Abstract: A method for treating perinatal mood disorders in women diagnosed with or at risk for the perinatal mood disorders. The method includes administering a digital therapeutic to the subject, the digital therapeutic configured to provide cognitive behavioral therapy content to the subject to treat the perinatal mood disorders, wherein the perinatal mood disorders are treated, thereby causing the subject to exhibit an improvement upon completion of the cognitive behavioral therapy content relative to a control subject that was not administered the digital therapeutic. In some embodiments, the digital therapeutic can be administered in conjunction with a pharmacotherapeutic.

Abstract: A pharmaceutical composition of Quercetin nanosuspension comprising Quercetin dihydrate, about 0.1% w/w to 10% w/w of Poloxamer, about 0.1% w/w to 10% w/w of polyvinyl pyrrolidone, and about 0.1% w/w to 10% w/w of polyethylene glycol. A method for preparing Quercetin nanosuspension, comprising the steps of dissolving polyvinyl pyrrolidone, Poloxamer, and polyethylene glycol in purified water, adding Quercetin to the above solution, subjecting the resulting mixture to bead milling to form Quercetin nanocrystals or nanosuspension.

Abstract: Systems and methods for analyzing users interacting with or utilizing a digital therapeutic system are disclosed. The systems and methods include receiving audio and video of the user in connection with the user interacting with or receiving digital therapy content, determining speech data or other user data from the audio and video, determining a mental state for the user based on the determined data, and taking an action based on the determined mental state, such as providing the determined mental state to at least one of the user or a healthcare provider associated with the user.

Abstract: Systems and methods for analyzing users interacting with or utilizing a digital therapeutic system are disclosed. The systems and methods include receiving audio and video of the user in connection with the user interacting with or receiving digital therapy content, determining speech data or other user data from the audio and video, determining a mental state for the user based on the determined data, and taking an action based on the determined mental state, such as providing the determined mental state to at least one of the user or a healthcare provider associated with the user.

Abstract: A system and method for prescribing education is disclosed herein. The system includes an electronic medical record database, a user input device, a content source, and an education engine. The education engine receives a patient physiological condition from the electronic medical records database, patient information from the user input device, and selects medical education content from the content source in order to create a prescribed education plan. A method of treating a patient with prescribed education is also disclosed herein. The method includes the steps of obtaining a patient understanding level, obtaining a patient literacy level, and obtaining a patient physiological condition. The patient physiological condition and understanding level are used select medical education content for the patient education. The patient literacy level is used to select a media for the patient education.

Abstract: A system and method for providing adaptive decision support is disclosed in further detail herein. An embodiment of this system includes a local outcome report that documents a medical outcome, a difference engine that compares the local outcome report to a national outcome report and generates a localized rule, and a rule engine that receives patient data and applies the localized rule from the difference engine to the patient data to produce a prescribed treatment. An embodiment of the method disclosed herein begins with receiving local patient data and outcome data. The outcome data is compared to national outcome data and a local rule is generated from the comparison. Next, the local patient and the outcome data is analyzed and a standard rule is generated based upon this analysis. The standard rule and the local rule are then applied to the local patient data to generate a prescribed treatment.