Sequential Pattern Mining to Predict Medical In-Hospital Mortality from Administrative Data: Application to Acute Coronary Syndrome

Table 2

Two examples of the most frequently mined contextual sequential patterns in ACS trajectories together with their corresponding support.

Sequential pattern	Support
Man and 45–65 years and >5 stays
<(Chronic ischemic heart disease)>	42.4
<(Angina pectoris)>	32.6
<(AMI)>	29.5
<(Angina pectoris) (angina pectoris)>	6.1
<(Angina pectoris) (chronic ischemic heart disease)>	4.4
<(Chronic ischemic heart disease) (chronic ischemic heart disease) (chronic ischemic heart disease)>	1.8
Woman and >65 years and ≤5 stays
<(AMI)>	45.4
<(Angina pectoris)>	25.2
<(Chronic ischemic heart disease)>	24.5
<(Chronic ischemic heart disease) (chronic ischemic heart disease)>	2.7
<(AMI) (chronic ischemic heart disease)>	1.9
<(AMI) (AMI)>	1.9