Abstract: Disclosed herein is a machine learning platform and system for data analysis including for purposes of providing digital evaluations and therapeutics.

Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.

Abstract: Methods and compositions for providing control over a subject's body, include methods and compositions for enhancing the ability of a subject's body to lose weight, or for inducing weight loss in the subject's body. Such methods and compositions may induce thermogenesis in the adipocytes of a subject's body, enhancing the subject's metabolism, inhibit adipogenesis in adipocytes of the individual, and reduce the subject's cravings for food, the subject's appetite and/or the amount of food consumed by the subject. Such a composition may include African mango (Irvinia gabonensis) seed extract, citrus fruits extract from Citrus aurantium, Citrus sinensis, and/or Citrus paradisi (standardized to 5% synephrine and 80% bioflavonoids), Coleus forskholi root extract, and a source of dihydrocapsiate. The composition may be administered with a protein supplement, such as a whey protein supplement (e.g., a hydrolyzed whey protein supplement).

Abstract: Systems and methods of the present disclosure are directed to neural stimulation via non-invasive sensory stimulation. Non-invasive sensory stimulations can comprise audio stimulation, visual stimulation, mechanical stimulation, or a combination thereof. The combination and/or sequence of one or more of audio, visual, and mechanical brain stimulations can adjust, control or otherwise manage the frequency of the neural oscillations to provide beneficial effects to one or more cognitive states or cognitive functions of the brain, while mitigating or preventing adverse consequences on a cognitive state or cognitive function that stems from, for example, sleep deprivation, stress, hormonal imbalance, or other physical, physiological, or psychological conditions. In doing so, the present systems and methods can improve the cognitive potential of a person.

Abstract: The present disclosure describes a method for neuromodulating a subject, comprising providing (i) a cognitively engaging content, and (ii) a gamma oscillation inducing waveform, wherein said gamma oscillation inducing waveform: comprises an intensity that renders said gamma oscillation inducing waveform imperceptible to said subject; and causes a therapeutic improvement in a cognitive function, thereby neuromodulating said subject.

Abstract: Disclosed herein is a machine learning platform and system for data analysis including for purposes of providing digital evaluations and therapeutics.

Abstract: Systems and methods of the present disclosure are directed to neural stimulation via non-invasive sensory stimuli. The non-invasive sensory stimuli can reduce neuroinflammation, improving synaptic plasticity and stimulating neural networking, and improving microglial-mediated clearance of cerebral insults, which would otherwise contribute to the progression of brain atrophy, by inducing synchronized gamma oscillations in at least one region of a brain in a subject. Stimulations can adjust, control or otherwise manage the frequency of the neural oscillations to provide beneficial effects to one or more cognitive states or cognitive functions of the brain, while mitigating or preventing adverse consequences on a cognitive state or cognitive function that stem from progression of brain atrophy.

Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.

Abstract: Machine learning-based systems and platforms use digital data to process data sets to generate assessments including classifications and/or regressions.

Abstract: The methods and apparatus disclosed herein can evaluate a subject for a developmental condition or conditions and provide improved sensitivity and specificity for categorical determinations indicating the presence or absence of the developmental condition by isolating hard-to-screen cases as inconclusive. The methods and apparatus disclosed herein can be configured to be tunable to control the tradeoff between coverage and reliability and to adapt to different application settings and can further be specialized to handle different population groups.

Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.

Abstract: The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

Abstract: Disclosed herein are platforms, systems, devices, methods and media for model optimization and data analysis using machine learning. Input data can be processed and analyzed to identify relevant discriminating features, which can be modeled using a plurality of machine learning models. A computing device can be configured with one or more optimized models for categorizing input data.

Abstract: The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

Abstract: The methods and apparatus disclosed herein can diagnose or identify a subject as at risk of having one or more developmental disorders with fewer questions, decreased amounts of time, and determine a plurality of developmental disorders, and provide clinically acceptable sensitivity and specificity in a clinical environment. The methods and apparatus disclosed herein can be configured to diagnose or determine the subject as at risk of a developmental disorder among a plurality of developmental disorders, and decreasing the number of questions presented can be particularly helpful where a subject presents with a plurality of possible developmental disorders. A processor can be configured with instructions to identify a most predictive next question, such that a person can be diagnosed or identified as at risk with fewer questions.

Abstract: The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

Abstract: A drink includes an edible liquid or semisolid preparation and transfer factor. The drink may also include lactoferrin and one or more preservatives. An edible preparation includes a fruit component and transfer factor. The fruit component may include at least one oligoproanthocyanidin-containing fruit. The edible preparation may also include lactoferrin. One or more preservatives may also be included in the edible preparation. The drink or the edible preparation may be sterilized or pasteurized.

Abstract: The methods and apparatus disclosed herein can diagnose or identify a subject as at risk of having one or more developmental disorders with fewer questions, decreased amounts of time, and determine a plurality of developmental disorders, and provide clinically acceptable sensitivity and specificity in a clinical environment. The methods and apparatus disclosed herein can be configured to diagnose or determine the subject as at risk of a developmental disorder among a plurality of developmental disorders, and decreasing the number of questions presented can be particularly helpful where a subject presents with a plurality of possible developmental disorders. A processor can be configured with instructions to identify a most predictive next question, such that a person can be diagnosed or identified as at risk with fewer questions.

Abstract: The digital personalized medicine system uses digital data to assess or diagnose symptoms of a subject to provide personalized or more appropriate therapeutic interventions and improved diagnoses. The use of prioritized questions and answers with associated feature importance can be used to assess mental function and allow a subject to be diagnosed with fewer questions, such that diagnosis can be repeated more often and allow the dosage to be adjusted more frequently. Pharmacokinetics of the subject can be estimated based on demographic data and biomarkers or measured, in order to determine a treatment plan for the subject. Also, biomarkers can be used to determine when the patient may be at risk for experiencing undesirable side effects and the treatment plan adjusted accordingly.

Abstract: Disclosed herein are compositions of antipurinergic agents and methods of use thereof for treating cognitive developmental disorders and autism spectrum disorders (ASD) in patients in need thereof.