Activity based medical monitoring

A method of determining medical conditions of users participating in a social networking service, the method executed by a computer system and comprising:

• automatically monitoring destinations and user activities performed at the destinations of a first user via a first electronic device of the first user;
• receiving user information comprising a first user activity performed at at least one of the destinations upon a user arriving at the at least one destination;
• automatically learning activity patterns for the first user activity by automatically associating the user information with the at least one of the destinations, automatically determining a user activity context for the first user activity, and automatically comparing a further context of each of a plurality of further user arrivals to the at least one of the destinations to the user activity context, wherein the activity patterns comprise a communication pattern, a mobility pattern, a visitation pattern, a sleep pattern, an eating pattern and/or an exercise pattern, at a location and/or with one or more community members;
• automatically determining a decrease in occurrences of the first user activity during a first predetermined time period;
• automatically analyzing the decrease to identify a deviation significance, wherein the decrease and/or the deviation significance is automatically determined using an inference engine, and analyzing the decrease comprises correlating the decrease to the first user being at a current destination during the first predetermined time period, and analyzing the decrease comprises identifying a temporary change in the learned activity patterns as a function of the current destination not allowing for the first user activity at the at least one of the destinations;
• automatically determining a second decrease in occurrences of the first user activity over a second predetermined time period after the first predetermined time period;
• automatically analyzing the second decrease to identify a second deviation significance, wherein the second decrease and/or the second deviation significance is automatically determined using the inference engine;
• automatically correlating the second deviation significance to a possible medical condition;
• and
• automatically alerting the first user via the first electronic device or a second user via a second electronic device of the possible medical condition upon the second deviation significance meeting a predetermined threshold, wherein the alerting includes a visual representation to the first electronic device and/or the second electronic device, and the second user is a medical professional, a close community member, and/or a community member engaged in a similar user activity.