Abstract: A prediction system may train a neural network model to analyze data to predict sentiments associated with the data and a measure of incompleteness of the data. The prediction system may obtain communication data regarding a communication session between a first device and a second device. The communication data is obtained via a network. The prediction system may provide the communication data as an input to the trained neural network model. The prediction system may determine, using the trained neural network model, a first set of sentiments associated with the first device and a second set of sentiments associated with the second device. The prediction system may determine, using the trained neural network model, a measure of incompleteness of the communication data based on the first set of sentiments and the second set of sentiments. The prediction system may perform an action based on the measure of incompleteness.

Abstract: A method and system for managing health care patient record data including identifying and conveying recordation and temporal inconsistencies in health care patient data pertaining to chronic illnesses. An embodiment of the present invention includes identifying a first health care encounter date on which a chronic illness is recorded in a patient's digital health care data and determining if the chronic illness was recorded in the patient's digital health care data for each subsequent health care encounter. Some embodiments also identify the stage of the chronic illness at each encounter to determine if and how the condition of the chronic illness has changed. Some embodiments generate alerts to inform users when a preexisting chronic illness is not subsequently identified and/or if the subsequent diagnosis of the chronic illness indicates that the condition of the chronic illness has changed by some predetermined amount.

Abstract: In some implementations, a device may generate, using a machine learning model, a first output relating to an event during a first period of time. The machine learning model may be trained using training data. The device may obtain actual data relating to the event during a second period of time that precedes the first period of time. The device may generate updated training data based on the training data and the actual data. The device may train, using the updated training data, the machine learning model to generate an updated machine learning model. The device may generate, using the updated machine learning model, a second output relating to the event during a third period of time. The device may cause one or more resources to be allocated based on the second output.

Abstract: A method of treating a patient to prevent heart failure readmission can include identifying one or more risk factors for the patient, and selecting one or more interventions relating to the one or more risk factors in a graphical user interface (GUI) of a treatment support system. The method also includes receiving a statistical score of the one or more interventions to determine the effect of the one or more selected interventions on heart failure readmission, and treating the patient as a function of the received statistical score using the one or more interventions.

Abstract: A method and system for managing health care patient record data including identifying and conveying recordation and temporal inconsistencies in health care patient data pertaining to chronic illnesses. An embodiment of the present invention includes identifying a first health care encounter date on which a chronic illness is recorded in a patient's digital health care data and determining if the chronic illness was recorded in the patient's digital health care data for each subsequent health care encounter. Some embodiments also identify the stage of the chronic illness at each encounter to determine if and how the condition of the chronic illness has changed. Some embodiments generate alerts to inform users when a preexisting chronic illness is not subsequently identified and/or if the subsequent diagnosis of the chronic illness indicates that the condition of the chronic illness has changed by some predetermined amount.

Abstract: A method for managing health care patient record data including: associating, by a processor, native health care patient record data of a first patient stored in a database to a plurality of data fields, wherein the native health care patient record data of the first patient represents the first patient's health care record; assigning, by a processor, a relative importance weight score to each of the plurality of data fields; and generating, by a processor, a record strength score of the first patient's health care record based on the relative importance weight score assignments. The record strength score indicates a percentage of the first patient's health care record that contains important native health care patient record data.

Abstract: A method for managing health care patient record data including: associating, by a processor, native health care patient record data of a first patient stored in a database to a plurality of data fields, wherein the native health care patient record data of the first patient represents the first patient's health care record; assigning, by a processor, a relative importance weight score to each of the plurality of data fields; and generating, by a processor, a record strength score of the first patient's health care record based on the relative importance weight score assignments. The record strength score indicates a percentage of the first patient's health care record that contains important native health care patient record data.

Abstract: A method of treating a patient to prevent heart failure readmission can include identifying one or more risk factors for the patient, and selecting one or more interventions relating to the one or more risk factors in a graphical user interface (GUI) of a treatment support system. The method also includes receiving a statistical score of the one or more interventions to determine the effect of the one or more selected interventions on heart failure readmission, and treating the patient as a function of the received statistical score using the one or more interventions.

Abstract: A method for managing health care patient record data including: associating, by a processor, native health care patient record data of a first patient stored in a database to a plurality of data fields, wherein the native health care patient record data of the first patient represents the first patient's health care record; assigning, by a processor, a relative importance weight score to each of the plurality of data fields; and generating, by a processor, a record strength score of the first patient's health care record based on the relative importance weight score assignments. The record strength score indicates a percentage of the first patient's health care record that contains important native health care patient record data.