Methods and systems for comprehensive patient screening

1 . A method comprising:

receiving, via a user device, a plurality of responses to a plurality of screening questions from a user, wherein each screening question is associated with a symptomatic indicator of a plurality of symptomatic indicators;

determining, by the user device for each symptomatic indicator of the plurality of symptomatic indicators, based on the response to each of the plurality of screening questions, a score;

receiving, at the user device from an interface associated with the user device, one or more physiological or behavioral signals captured by one or more sensors,

wherein the physiological or behavioral signals comprise at least one of audio sensor data, video sensor data, or motion sensor data;

determining, by the user device based on the score for each symptomatic indicator of the plurality of symptomatic indicators and the one or more physiological or behavioral signals, a profile comprising the aggregated user health data;

sending the profile comprising aggregated user health data to a computing device;

receiving, from the computing device based on the profile, an alert condition including an indication that the user is at risk of an emergency medical condition, wherein the computing device comprises a machine learning model comprising a neural network trained on profiles and corresponding prior diagnoses and is configured to determine the alert condition; and

sending, from the user device to a clinical device, the alert condition.

2 . The method of claim 1 , wherein storing the profile comprises:

establishing a communication session between the user device and a computing device system;

receiving, by the computing device, a device identifier of the user device and a user identifier of the user;

authenticating, based on a device identifier, the user device;

authenticating, based on the user identifier, the user; and

storing, based on authenticating the user device and the user, the profile.

3 . The method of claim 1 , further comprising encrypting at least one of, the device identifiers, the user identifier, or the score for each response of the plurality of responses.

4 . The method of claim 1 , wherein the alert condition for the user is further determined based on at least one score for a symptomatic indicator of the plurality of symptomatic indicators.

5 . The method of claim 4 , wherein the alert condition is determined based on the score satisfying a threshold.

6 . The method of claim 5 , further comprising:

determining a clinician associated with a type of the alert condition; and

determining, based on the clinician, the clinical device.

7 . The method of claim 1 , wherein the user device comprises one or more of, a mobile phone, a tablet computer, a laptop computer, or a desktop computer.

8 . The method of claim 1 , wherein the interface comprises one or more of an accelerometer, a pedometer, a geographical position sensing (GPC) module, an oximeter, or a tactile sensor.

9 . The method of claim 1 , further comprising sending, based on a score of the plurality of scores satisfying a threshold, a notification.

10 . The method of claim 1 , further comprising sending, based on a signal of the one or more signals satisfying a threshold, a notification.

11 . The method of claim 1 , wherein presenting, via the user device, the plurality of screening questions comprises presenting the plurality of screening questions via an application running on the user device.

12 . The method of claim 1 , wherein the plurality of screening questions are associated with two or more of occupational and regional exposure, military service history, somatic symptoms, physical injury, illness, pain, post-traumatic stress disorder (PTSD) symptoms, behavior, depression symptoms, and social interactions.

13 . The method of claim 1 , wherein determining, for each symptomatic indicator of the plurality of symptomatic indicators, based on the response to each of the plurality of screening questions, the score comprises:

determining, based on the symptomatic indicator, a scale; and

scaling, based on the scale, the response to each of the plurality of screening questions,

wherein the scaled response represents the score.

14 . The method of claim 1 , further comprising:

determining, for each of a plurality of user, a dataset comprising a score for each symptomatic indicator of the plurality of symptomatic indicators and one of, an indication of a possible diagnosis of a medical issue related to the symptomatic indicator or an indication of no likely diagnosis of a medical issue related to the symptomatic indicator;

determining, based on the dataset, a training dataset; and

training, based on the training dataset, a machine learning module to determine a likelihood that another user will have a diagnosis of an issue related to the symptomatic indicator based on the score for the symptomatic indicator.

15 . A method comprising:

receiving, via a user device, a plurality of responses to a plurality of screening questions from a user;

determining, for each response of the plurality of responses, a score;

receiving, from an interface associated with the user device, one or more physiological or behavioral signals captured by one or more sensors, wherein the physiological or behavioral signals comprise at least one of audio sensor data, video sensor data, or motion sensor data;

determining, based on the score for each response of the plurality of responses and the one or more physiological or behavioral signals, a profile comprising aggregated user health data;

sending the profile comprising the aggregated user health data to a computing device;

receiving, from the computing device based on the profile, an alert condition including an indication that the user is at risk of an emergency medical condition, wherein the computing device comprises a machine learning model comprising a neural network trained on profiles and corresponding prior diagnoses and is configured to determine the alert condition comparing the profile to a plurality of profiles and determining, based on comparing the profile to a plurality of profiles, wherein each profile of the plurality of profiles is associated with a respective user of a plurality of users, wherein each target area is associated with a symptomatic indicator, wherein the symptomatic indicator is associated with the alert condition; and

sending, from the user device to a clinical device, the alert condition.

16 . The method of claim 15 further comprising, causing display of the target area.

17 . The method of claim 15 , wherein the user device comprises one or more of, a mobile phone, a tablet computer, a laptop computer, or a desktop computer.

18 . The method of claim 15 , wherein the interface comprises one or more of an accelerometer, a pedometer, a geographical position sensing (GPC) module, an oximeter, or a tactile sensor.

19 . An apparatus comprising:

one or more processors; and

memory storing processor-executable instructions that, when executed by the one or more processors, cause the apparatus to:

receive a plurality of responses to a plurality of screening questions from a user;

determine, for each response of the plurality of responses, a score;

receive, from an interface associated with the user device, one or more physiological or behavioral signals captured by one or more sensors,

wherein the physiological or behavioral signals comprise at least one of audio sensor data, video sensor data, or motion sensor data;

determine, based on the score for each response of the plurality of responses and the one or more physiological or behavioral signals, a profile comprising aggregated user health data;

send the profile comprising the aggregated user health data to a computing device;

receive, from the computing device based on the profile, an alert condition including an indication that the user is at risk of an emergency medical condition, wherein the computing device comprises a machine learning model comprising a neural network trained on profiles and corresponding prior diagnoses and is configured to determine the alert by comparing the profile to a plurality of profiles and determining, based on comparing the profile to a plurality of profiles, a target area, wherein each profile of the plurality of profiles is associated with a respective user of a plurality of users, wherein each target area is associated with a symptomatic indicator; and

send, to a clinical device, the alert condition.