Abstract: Altitude and/or motion data is collected from one or more devices associated with multiple application users, and the altitude and/or motion data is utilized to generate machine learning-based predictive model training data. One or more machine learning-based predictive models are trained using the machine learning-based predictive model training data. Current altitude and/or motion data is collected from one or more devices associated with a current user of an application and is provided to the one or more trained machine learning-based predictive models. Predictions regarding the physical and/or psychological state of the user are received from the one or more trained machine learning-based predictive models and analyzed to identify changes or anomalies in the user's physical and/or psychological state. Upon identification of changes or anomalies in the user's physical and/or psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Through the one or more applications, the user is provided with interactive content, and data related to aspects of the user's interaction with the provided content is collected. The collected interaction data is analyzed to remotely identify and monitor changes or anomalies in the psychological state of the user. Upon identification of changes or anomalies in the user's psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Through the one or more applications, the user is provided with interactive content, and data related to aspects of the user's interaction with the provided content is collected. The collected interaction data is analyzed to remotely identify and monitor changes or anomalies in the psychological state of the user using machine learning-based models. Upon identification of changes or anomalies in the user's psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Altitude and/or motion data is collected from one or more devices associated with the user, and the device altitude and/or motion data is utilized to identify physical activities being performed by the user. The device altitude and/or motion data is further analyzed to determine physical activity count data, physical activity speed, velocity, and/or acceleration data, and physical activity length data. The physical activity data is then analyzed to identify and monitor changes or anomalies in the physical and/or psychological state of the user using average physical activity data. Upon identification of changes or anomalies in the user's physical and/or psychological state, one or more actions are taken to assist the user.

Abstract: A protocol generation system for a first culture takes historical therapeutic protocol data associated with a first culture as input data, and outputs maximally effective therapeutic protocols for patients associated with the first culture. The maximally effective therapeutic protocols for patients associated with the first culture are provided to a protocol translation module, resulting in the generation of translated therapeutic protocols for cultures other than the first culture. The translated therapeutic protocols are provided to a culturally sensitive protocol translation module, which transforms the translated therapeutic protocols into protocols that are culturally sensitive to cultures other than the first culture. Individual protocol generation systems associated with cultures other than the first culture are utilized to generate maximally effective therapeutic protocols for patients associated with cultures other than the first culture.

Abstract: Therapeutic imagery is selected for administration to a patient, and the therapy is administered to the patient. The patient's responses to the therapeutic imagery are monitored, collected, and correlated with the associated therapeutic imagery attribute data to generate data indicating the effectiveness of the imagery. The therapeutic imagery effectiveness data is used as training data to train one or more machine learning based therapeutic imagery effectiveness prediction models. Data associated with one or more new therapeutic imagery attributes is provided as input to one or more of the trained therapeutic imagery effectiveness prediction models, which generates predicted therapeutic imagery effectiveness data for the new therapeutic imagery. The therapeutic imagery effectiveness data is analyzed to determine and select one or more effective therapeutic imagery attributes, resulting in generation of maximally effective therapeutic imagery.

Abstract: A therapy is selected for administration to a patient, and the therapy is administered to the patient according to one or more therapeutic protocols. The patient's responses to the therapeutic protocols are monitored, collected, and correlated with the associated protocol data to generate data indicating the effectiveness of the protocols. The protocol effectiveness data is used as training data to train one or more machine learning based therapeutic protocol effectiveness prediction models. Data associated with one or more new protocols is provided as input to one or more of the trained therapeutic protocol effectiveness prediction models, which generates predicted protocol effectiveness data for the new protocols. The protocol effectiveness data is analyzed to determine and select one or more effective therapeutic protocols, resulting in generation of one or more maximally effective protocols.

Abstract: A protocol generation system for a first culture takes historical therapeutic protocol data associated with a first culture as input data, and outputs maximally effective therapeutic protocols for patients associated with the first culture. The maximally effective therapeutic protocols for patients associated with the first culture are provided to a protocol translation module, resulting in the generation of translated therapeutic protocols for cultures other than the first culture. The translated therapeutic protocols are provided to a culturally sensitive protocol translation module, which transforms the translated therapeutic protocols into protocols that are culturally sensitive to cultures other than the first culture. Individual protocol generation systems associated with cultures other than the first culture are utilized to generate maximally effective therapeutic protocols for patients associated with cultures other than the first culture.

Abstract: A therapy is selected for administration to a patient, and the therapy is administered to the patient according to one or more therapeutic protocols. The patient's responses to the therapeutic protocols are monitored, collected, and correlated with the associated protocol data to generate data indicating the effectiveness of the protocols. The protocol effectiveness data is used as training data to train one or more machine learning based therapeutic protocol effectiveness prediction models. Data associated with one or more new protocols is provided as input to one or more of the trained therapeutic protocol effectiveness prediction models, which generates predicted protocol effectiveness data for the new protocols. The protocol effectiveness data is analyzed to determine and select one or more effective therapeutic protocols, resulting in generation of one or more maximally effective protocols.

Abstract: Therapeutic imagery is selected for administration to a patient, and the therapy is administered to the patient. The patient's responses to the therapeutic imagery are monitored, collected, and correlated with the associated therapeutic imagery attribute data to generate data indicating the effectiveness of the imagery. The therapeutic imagery effectiveness data is used as training data to train one or more machine learning based therapeutic imagery effectiveness prediction models. Data associated with one or more new therapeutic imagery attributes is provided as input to one or more of the trained therapeutic imagery effectiveness prediction models, which generates predicted therapeutic imagery effectiveness data for the new therapeutic imagery. The therapeutic imagery effectiveness data is analyzed to determine and select one or more effective therapeutic imagery attributes, resulting in generation of maximally effective therapeutic imagery.

Abstract: Described herein are various technologies pertaining to presenting training data for a task performed using an electronic health records application (EHR) to healthcare workers. A context for a task to be performed within the EHR is transmitted to a server from a client EHR. The context includes data indicative of or pertaining to a healthcare worker using the client EHR, an element of a graphical user interface (GUI) of the client EHR, or other data indicative of the task to be performed within the EHR. The server transmits a list of training materials to the client EHR based upon the context, where the training materials comprise data pertaining to performance of one or more tasks by way of the client EHR. Responsive to receiving the list, the client EHR displays an indication of a training material in the training materials within the GUI of the client EHR.

Abstract: A prescription digital therapeutic (PDT) system is provided to patients/users suffering from gastrointestinal (GI) and/or inflammatory health conditions, wherein the PDT system allows guided behavioral therapy and skills training to be administered in a convenient and flexible, yet structured fashion, via a system associated with an application such as a mobile application. Guided behavioral therapy technologies may be based at least in part on cognitive behavioral therapy (CBT) techniques to allow for development of a skillset for treating gastrointestinal (GI) and/or inflammatory diseases, disorders and/or conditions, and for managing stress and/or other psychological symptoms associated with such diseases, disorders and/or conditions. Patient interactions with the PDT system are monitored to control progression through the system content and to continually refine one or more personalized intervention regimens associated with the guided behavioral therapy.

Abstract: A prescription digital therapeutic (PDT) system is provided to patients/users, wherein the PDT system allows guided behavioral therapy and skills training to be administered in a convenient and flexible, yet structured fashion, via a system associated with an application such as a mobile application. Guided behavioral therapy technologies may be based at least in part on cognitive behavioral therapy (CBT) techniques to allow for development of a skillset for treating a physiological disease, disorder and/or condition, and for managing stress and/or other psychological symptoms associated with such disease, disorder and/or condition. Patient interactions with the PDT system are monitored to control progression through the system content and to continually refine one or more personalized intervention regimens associated with the guided behavioral therapy.

Abstract: A prescription digital therapeutic (PDT) system is provided to patients/users suffering from gastrointestinal (GI) and/or inflammatory health conditions, wherein the PDT system allows guided behavioral therapy to be administered in a convenient and flexible, yet structured fashion, in combination with one or more non-behavioral therapies. Guided behavioral therapy technologies may be based at least in part on cognitive behavioral therapy (CBT) techniques to allow for development of a skill set for treating gastrointestinal (GI) and/or inflammatory diseases, disorders and/or conditions, and for managing stress and/or other psychological symptoms associated with such diseases, disorders and/or conditions. Non-behavioral therapies include administration of pharmaceuticals compositions, nutraceutical compositions and/or other therapies associated with a variety of medical devices.

Abstract: Altitude and/or motion data is collected from one or more devices associated with multiple application users, and the altitude and/or motion data is utilized to generate machine learning-based predictive model training data. One or more machine learning-based predictive models are trained using the machine learning-based predictive model training data. Current altitude and/or motion data is collected from one or more devices associated with a current user of an application and is provided to the one or more trained machine learning-based predictive models. Predictions regarding the physical and/or psychological state of the user are received from the one or more trained machine learning-based predictive models and analyzed to identify changes or anomalies in the user's physical and/or psychological state. Upon identification of changes or anomalies in the user's physical and/or psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Altitude and/or motion data is collected from one or more devices associated with the user, and the device altitude and/or motion data is utilized to identify physical activities being performed by the user. The device altitude and/or motion data is further analyzed to determine physical activity count data, physical activity speed, velocity, and/or acceleration data, and physical activity length data. The physical activity data is then analyzed to identify and monitor changes or anomalies in the physical and/or psychological state of the user using baseline physical activity data. Upon identification of changes or anomalies in the user's physical and/or psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Altitude and/or motion data is collected from one or more devices associated with the user, and the device altitude and/or motion data is utilized to identify physical activities being performed by the user. The device altitude and/or motion data is further analyzed to determine physical activity count data, physical activity speed, velocity, and/or acceleration data, and physical activity length data. The physical activity data is then analyzed to identify and monitor changes or anomalies in the physical and/or psychological state of the user using average physical activity data. Upon identification of changes or anomalies in the user's physical and/or psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Through the one or more applications, the user is provided with interactive content, and data related to aspects of the user's interaction with the provided content is collected. The collected interaction data is analyzed to remotely identify and monitor changes or anomalies in the psychological state of the user using machine learning-based models. Upon identification of changes or anomalies in the user's psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Through the one or more applications, the user is provided with interactive content, and data related to aspects of the user's interaction with the provided content is collected. The collected interaction data is analyzed to remotely identify and monitor changes or anomalies in the psychological state of the user based on historical user interaction data. Upon identification of changes or anomalies in the user's psychological state, one or more actions are taken to assist the user.

Abstract: An application user is granted access to one or more applications that provide the user with information and assistance. Through the one or more applications, the user is provided with interactive content, and data related to aspects of the user's interaction with the provided content is collected. The collected interaction data is analyzed to remotely identify and monitor changes or anomalies in the psychological state of the user based on average user interaction data. Upon identification of changes or anomalies in the user's psychological state, one or more actions are taken to assist the user.