Abstract:
A network has a plurality of user accounts and a network enabled analysis system, which can receive selected information from a first user. A pattern can be established based on the received information, and responsive thereto a comparable pattern can be sought. A data base of patterns can be provided to which the established pattern can be compared using pattern recognition techniques. In one aspect, a processed pattern can be generated. The processed pattern can be compared to patterns of selected information received from other users in the network. In response to finding a comparable pattern, feedback can be provided to the first user.

Description:
FIELD 
       [0001]    The application pertains to systems and methods of providing feedback relative to predetermined events. More particularly, the application pertains to finding relationships among events and to providing a user with possible suggestions as to proceeding based on the experiences of other users. 
       BACKGROUND 
       [0002]    On-line social networks have become very popular vehicles for many individuals to easily communicate information to one another. They provide environments which enable users to connect to and communicate with other users. Examples of such networks include Facebook and LinkedIn. 
         [0003]    Social networks such as Facebook and LinkedIn, try to utilize an individual&#39;s contacts to propose new links to other individuals. In such systems, the goal is to connect network users. Such connections reflect a single dimension of who knows who to suggest a user might know someone. 
         [0004]    It would be useful to move beyond existing types of systems and be able to associate one or more patterns of useful information that originate with a user with similar patterns that originate with other users in the community. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0005]      FIG. 1  illustrates a diagram of a system in accordance herewith; and 
           [0006]      FIG. 2  illustrates aspects of a method which could be implemented by the system of  FIG. 1 . 
       
    
    
     DETAILED DESCRIPTION 
       [0007]    While disclosed embodiments can take many different forms, specific embodiments thereof are shown in the drawings and will be described herein in detail with the understanding that the present disclosure is to be considered as an exemplification of the principles thereof as well as the best mode of practicing same, and is not intended to limit the application or claims to the specific embodiment illustrated. 
         [0008]    In embodiments hereof, relationships among various events a user has experienced can be found, then, other users who have experienced similar event patterns, can be found and possible observations of interest can be provided to the user. 
         [0009]    In one aspect, event categories, event types and events can be established to form a plan. Table 1, attached hereto, illustrates an exemplary plan having several categories of events, event types and events in connection with a diagnosis of Type 2 diabetes. Other event categories, event types or events can be defined and come within the spirit and scope hereof. 
         [0010]    Event types have specific factual events associated with them. For example, if the category is exercise, as in Table 1, event types can include walking running biking or the like. Events can include durations and, or types of exercise. 
         [0011]    The observed or recognized events can be processed, in accordance herewith, to form a characteristic pattern. That pattern can be processed, with respect to pre-established patterns associated with the event type. Other users of the network can be solicited for patterns similar to the processed pattern which would support a conclusion of a specific event, such as a particular disease, or a particular type of bird or flying object. That feedback can be forwarded to the original user for consideration. 
         [0012]      FIGS. 1 ,  2  illustrate additional aspects of a system and method of the type noted above.  FIG. 1  illustrates an exemplary computer based communications network  10  in accordance herewith. 
         [0013]    The network  10  can be used simultaneously by a plurality of users, individuals A, B, . . . P who access the network  10  via respective internet enabled, preferably wireless, communication devices such as  14 - 1 , - 2 , - 3 , . . . -P. The devices  14 - i  can be implemented as smart phones, tablet computers, laptop computers or the like all without limitation. 
         [0014]    The devices  14 - i  communicate via a computer based network such as the Internet I with one or more network implementing servers  18  as would be understood by those of skill in the art. One or more analysis servers  20  are coupled directly, or via the Internet I to the network servers  18 . A data base  22  which can include pluralities of pre-stored patterns, as discussed below, is coupled to the analysis server  20 . It will be understood that the specific operational details of such social networks, except as described herein, are not limitations hereof. 
         [0015]      FIG. 2  illustrates a diagnostic process that a person, or user, such as user A, can carry out to obtain information as to a current condition. An exemplary platform which could be implemented by the server  18  can provide institutions such as health care providers, professional service corporations, and payors, such as insurance companies, with the ability to optimize the healthcare management large of populations by providing the families with actionable data. The below described process is a family centric solution that allows each family member to track any event (e.g. headache, BP, meal, run, dr. visit, fever, etc.) about their life. 
         [0016]    The collected data is actionable. Exemplary system  10  enables an institution to create a program which addresses a set of event types (for example, a. Wellness Program: Exercise, Diet, BP, Weight) to help improve the health of their respective population. For the user, system  10  can provide value outside of the programs by enabling them to discover things about themselves. 
         [0017]      FIG. 2  illustrates aspects of a process  100  wherein the designated Target Event Type is: Diagnosis as at  102 . In exemplary process  100  a user A has presented a group of events, as at  104  associated with an out of doors activity. 
         [0018]    The events  104  are factual statements that can, via system  10 , be reported to server  18 . Servers  18 ,  20  can process inputs from person, or user, A to attempt to find relationships among the events reported by person A as at  108 . 
         [0019]    The relationship, or pattern, as at  108  can be compared to and/or filtered, as at  110  using pre-store reference information or patterns from data base  22  to produce a set of processed or refined events as at  114 . Possible relationships can then be found, as at  116 , between the refined events  114  and either or both of pre-stored user related information from data base  22  or real time feedback from users such as users D, E. 
         [0020]    Where relationships are found, in this case leading to pre-existing diagnosis of lyme disease, presented by users D, E, as at  118 , that information can be forwarded to user A as at  120 . It will be understood that embodiments hereof can be implemented incorporating social networks. However, such networks are exemplary only and not limitations of the present system and method. 
         [0021]    In summary, unlike social networks, embodiments hereof are not trying to connect people, but to find patterns among people who are users of the network to help narrow relationships among events to present possible observations relevant to a user&#39;s interest. A pattern of interest can be represented as a group of event types and events. An event is something that can actually occur, an event instance, but could be anything. 
         [0022]    The exemplary process described above relates to the fact that Person A has experienced a suite of events and is not feeling well. Person A can choose to learn more about his/her condition by trying to have the system  10  suggest possible diagnosis event types based on reports of other people, or users, who experienced similar events. This suggests that first of all the events can be related, then matched to other people that have or had similar events with an associated diagnosis event type which could then be forwarded to Person A. 
         [0023]    From the foregoing, it will be observed that numerous variations and modifications may be effected without departing from the spirit and scope hereof. It is to be understood that no limitation with respect to the specific apparatus illustrated herein is intended or should be inferred. It is, of course, intended to cover by the appended claims all such modifications as fall within the scope of the claims. 
         [0024]    Further, logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Other steps may be provided, or steps may be eliminated, from the described flows, and other components may be add to, or removed from the described embodiments. 
         [0000]    
       
         
               
             
               
               
               
               
               
               
               
               
               
               
             
           
               
                 TABLE 1 
               
             
             
               
                   
               
               
                 PLAN 
               
               
                 Newly Diagnosed Type 2 Diabetes 
               
             
          
           
               
                   
                   
                   
                   
                   
                   
                   
                 Start 
                 Stop 
                   
               
               
                 Event 
                   
                   
                 Quan- 
                   
                 Explicit 
                   
                 Date/ 
                 Date/ 
                 Com- 
               
               
                 Category 
                 Event Type 
                 Event 
                 tity 
                 Interval 
                 Time 
                 Duration 
                 Time 
                 Time 
                 ment 
               
               
                   
               
               
                 Biometrics 
                 Glucose 
                 Glucose 
                   
                 Morning 
                   
                 Indefinite 
                 Day 0 
                   
                   
               
               
                   
                 Weight 
                 Weight 
                   
                 Weekly 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                 Blood Pressure 
                 Blood Pressure 
                   
                 Unscheduled 
                   
                 Indefinite 
                 Day 0 
               
               
                 Exercise 
                 Walking 
                 30 minutes Walking 
                   
                 3X/week 
                   
                 Indefinite 
                 Week 4, Sunday 
               
               
                   
                 Running 
                 30 minutes Running 
                   
                 3X/week 
                   
                 Indefinite 
                 Week 4, Sunday 
               
               
                   
                 Biking 
                 30 Minutes Biking 
                   
                 3X/week 
                   
                 Indefinite 
                 Week 4, Sunday 
               
               
                   
                 Strength Training 
                 30 Minutes Strength Training 
                   
                 3X/week 
                   
                 Indefinite 
                 Week 4, Sunday 
               
               
                   
                 Other 
                 30 Minutes Other Exercise 
                   
                 3X/week 
                   
                 Indefinite 
                 Week 4, Sunday 
               
               
                 Diet 
                 Meal 
                 Breakfast 
                   
                 Once per day 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                   
                 Lunch 
                   
                 Once per day 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                   
                 Dinner 
                   
                 Once per day 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                 Snack 
                 Morning Snack 
                   
                 Once per day 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                   
                 Afternoon Snack 
                   
                 Once per day 
                   
                 Indefinite 
                 Day 0 
               
               
                 Medications 
                 Metformin 
                 500 mg Metformin 
                   
                 Twice per day 
                   
                 Indefinite 
                 Day 0 
               
               
                 Appointment 
                 Physician 
                 &lt;Physician Name&gt; 
               
               
                   
                 Diabetes Educator 
                 &lt;EducatorName&gt; 
               
               
                   
                 Group Class 
                 Class A 
                   
                   
                 5:30 pm 
                 1 Time 
                 Week 1, Thursday 
               
               
                   
                   
                 Class B 
                   
                   
                 5:30 pm 
                 1 Time 
                 Week 2, Thursday 
               
               
                   
                   
                 Class C 
                   
                   
                 5:30 pm 
                 1 Time 
                 Week 3, Thursday 
               
               
                 Labs 
                 A1C 
                 A1C 
                   
                 Unscheduled 
               
               
                   
                 Fasting Glucose 
                 Fasting Glucose 
                   
                 Unscheduled 
               
               
                   
                 Glucose Tolerance 
                 Glucose Tolerance 
                   
                 Unscheduled 
               
               
                   
                 LDL 
                 LDL 
                   
                 Unscheduled 
               
               
                   
                 HDL 
                 HDL 
                   
                 Unscheduled 
               
               
                   
                 Triglycerides 
                 Triglycerides 
                   
                 Unscheduled 
               
               
                 Dental Care 
                 Brush 
                 Brush 
                   
                 Twice per day 
                   
                 Indefinite 
                 Day 0 
               
               
                   
                 Floss 
                 Floss 
                   
                 Twice per day 
                   
                 Indefinite 
                 Day 0 
               
               
                 Symptoms 
                 Frequent Urination 
                 Frequent Urnination 
                   
                 Unscheduled 
               
               
                   
                 Extreme Thirst 
                 Extreme Thirst 
                   
                 Unscheduled 
               
               
                   
                 Extreme Fatigue 
                 Extreme Fatigue 
                   
                 Unscheduled 
               
               
                   
                 Blurred Vision 
                 Blurred Vision - One Eye 
                   
                 Unscheduled 
               
               
                   
                   
                 Blurred Vision - Both Eyes 
                   
                 Unscheduled