Monitoring and determining the state of health of a user

1. A computer-implemented method comprising:

receiving, by one or more computer processors, monitoring data associated with monitoring a user, wherein the monitoring data is generated by one or more sensors;

analyzing, by one or more computer processors, visual monitoring data, from the one or more sensors, related to skin associated with neck and throat areas of the monitored user utilizing image recognition, wherein analyzing visual monitoring data related to the skin associated with the neck and throat areas of the monitored user utilizing image recognition further comprises:

identifying, by one or more computer processors, one or more changes related to the skin associated with the neck and throat areas of the monitored user including a texture change and identifying an irregularity of the skin;

determining, by one or more computer processors, a state of health of the monitored user by utilizing the image recognition analyses related to the skin associated with the neck and throat areas of the monitored user utilizing a machine learning model, wherein the machine learning model is associated with the monitored user utilizing known conditions associated with the monitored user, historical medical information corresponding to the monitored user, and information associated with a known state of health corresponding to the monitored user;

determining, by one or more processors, whether the determined state of health of the monitored user corresponds to a normal state of health for the user;

in response to determining that the determined state of health of the monitored user does not correspond to the normal state of health for the user, querying, by one or more processors, the user for additional information;

determining, by one or more computer processors, a level of urgency based upon the determined state of health of the monitored user, additional information received from the user in response to the query, the monitoring data, and querying a medical database;

modifying, by one or more computer processors, the machine learning model based on the additional information received from the user in response to the query; and

transmitting, by one or more computer processors, one or more respective notifications to one or more devices based, at least in part, on the determined state of health of the user and the corresponding level of urgency, wherein the one or more devices includes a device associated with the monitored user, and wherein a notification includes the determined state of health and the corresponding determined state of urgency associated with the monitored user.

2. The computer-implemented method of claim 1 , further comprising:

determining, by one or more computer processors, that the machine learning model does not determine a state of health of the monitored user;

receiving, by one or more computer processors, a dictate to update the machine learning model that generated a false-positive result by obtaining feedback from the monitored user; and

notifying, by one or more computer processors, the monitored user to provide feedback related to a state of health, as interpreted by the monitored user and information related to the received monitoring data.

3. The computer-implemented method of claim 1 , wherein the monitoring data further includes information related to one or more physical characteristics of neck and throat areas of the monitored user, selected from the group consisting of: information associated with a skin condition, a degree of tension in one or more muscles, one or more lumps under the skin, and a physical orientation of the monitored user; and

wherein the monitoring data further includes environmental factors associated with the monitored user, selected from the group consisting of: one or more items of apparel in proximity to the neck and throat areas, a temperature in proximity to the monitored user, and a level of stress associated with the monitored user.

4. The computer-implemented method of claim 1 , wherein querying the user for additional information further comprises:

querying, by one or more processors, the user for information associated with a sensor of the one or more sensors; and

receiving, by one or more processors, information indicating whether the sensor of the one or more sensors is operating correctly.

5. The computer-implemented method of claim 1 , wherein querying the user for additional information further comprises program instructions to:

querying, by one or more processors, the user for information associated with a current medical status of the user; and

receiving, by one or more processors, information indicating whether the user is currently experiencing a medical condition.

6. The computer-implemented method of claim 1 , wherein the monitoring data further includes information related to one or more physical characteristics of neck and throat areas of the monitored user, including, a degree of tension in one or more muscles.

7. The computer-implemented method of claim 1 , wherein the monitoring data further includes information related to one or more physical characteristics of neck and throat areas of the monitored user, including, a physical orientation of the monitored user.

8. The computer-implemented method of claim 1 , wherein the monitoring data further includes environmental factors associated with the monitored user, including one or more items of apparel in proximity to the neck and throat areas.

9. The computer-implemented method of claim 1 , wherein the monitoring data further includes environmental factors associated with the monitored user, including a level of stress associated with the monitored user.

10. The computer-implemented method of claim 1 , wherein the visual monitoring data comprises non-visible colors.

11. The computer-implemented method of claim 1 , wherein a first sensor of the one or more sensors comprises a temperature sensor embedded within a dental device, further comprising:

analyzing, by one or more computer processors, temperature data of items consumed by the monitored user; and

wherein determining the state of health of the monitored user further utilizes the temperature data analysis.