An often overlooked type of Analysis is Sequence Data Mining (or Sequential Pattern Mining).
Sequence Data Mining is a type of Analysis which aims in extracting patterns sequences of Events. We can also see Sequence Data Mining as an Associations Discovery Analysis with a Temporal Element.
Sequence Data Mining has many potential applications (Web Page Analytics, Complaint Events, Business Processes) but here today we will show an application for Health. I believe that this type of Analysis will become even more important as wearable technology will be used even more and therefore more Data of this kind will be generated.
Consider the following hypothetical scenario :
Sequence Data Mining is a type of Analysis which aims in extracting patterns sequences of Events. We can also see Sequence Data Mining as an Associations Discovery Analysis with a Temporal Element.
Sequence Data Mining has many potential applications (Web Page Analytics, Complaint Events, Business Processes) but here today we will show an application for Health. I believe that this type of Analysis will become even more important as wearable technology will be used even more and therefore more Data of this kind will be generated.
Consider the following hypothetical scenario :
A 30-year old Male patient complaints
about several symptoms which -for simplicity reasons- we will name them as Symptom1, Symptom2, Symptom3,etc.
His Doctor tries to identify what is going on and after the patient takes all necessary Blood work and finds no problems. After thorough evaluation the Doctor believes that his patient suffers from Chronic Fatigue Syndrome. Under the Doctor's supervision the patient will record his symptoms along with different supplements to understand more about his condition. Several events (e.g a Visit to the Gym, a stressful Event) will also be taken under consideration to see if any patterns emerge.
His Doctor tries to identify what is going on and after the patient takes all necessary Blood work and finds no problems. After thorough evaluation the Doctor believes that his patient suffers from Chronic Fatigue Syndrome. Under the Doctor's supervision the patient will record his symptoms along with different supplements to understand more about his condition. Several events (e.g a Visit to the Gym, a stressful Event) will also be taken under consideration to see if any patterns emerge.
-How Can we easily record Data for the scenario above?
-Can we extract sequences of events that occur more frequently than mere chance?
-Can we identify which sequences of Events / Food / Medication may potentially lead to specific Symptoms or to a lack of Symptoms?
Looking the problem through the eyes of a Data Scientist, We have :
A series of Events that happen during a day : A Stressful event, A
sedentary day, Cardio workouts, Weight Lifting, Abrupt Weather
Deterioration, etc
A Number of Symptoms : Headaches, "Brain Fog", Mood problems, Insomnia, Arthralgia, etc.
