## 2 Data Description
* Class B2 (non-progressors): This class involves progression data \(dx^{1}_{i,j}\) from 268 participants with KL 0 or 1 at the baseline, who had follow-up x-rays with no other incident of KL \(\geq\) 2 in any of their knees until the end of the OAI study. Output: Classification outputs 0 and 1 corresponding to assignments to classes B1 and B2, respectively. * Dataset C (FS3): Progressors vs. non-progressors using progression data within the first 24 months  
Figure 2: Flow chart of study design for dataset B. Input: Dataset C contains progression data \(dx_{i,j}^{2}\) within the first 24 months (until visit 2). The dataset contains 275 features that co-exist in visit 2 and the baseline, whereas the same methodology was used to calculate the features as given in Equation (1) using k = 2. The participants were divided into two equal categories (Figure 3), as follows:  
* Class C1 (KOA progressors): This class comprises of 239 participants who had KL 0 or 1 during the first 24 months, whereas a KOA incident (KL \(\geq\) 2) observed at visit 3 (36 months) or later during the OAI course in at least one of the two knees or in both. * Class C2 (non-progressors): This class involves 239 participants with KL grade 0 or 1 at baseline, with follow-up X-rays and no further incidents (KL \(\geq\) 2) for both of their knees. Output: Classification outputs 0 and 1 corresponding to assignments to classes C1 and C2, respectively. * Dataset D (FS4): Progressors vs. non-progressors using data from the baseline visit along with progression data within the first 12 months  
Input: Dataset D contains 957 features from both datasets A and B. Specifically, it consists of 957 features from the baseline (\(x_{i,j}^{0}\), \(j=1,\ldots,724\)) along with progression data (\(dx_{i,j}^{1}\), \(j=1,\ldots,233\)) within  
Figure 3: Flow chart of study design for dataset C.  
the first 12 months. The list with the selected features from dataset D is given in Appendix A. After the application of data sampling, the participants were divided into two equal categories (Figure 4), as follows: Class D1 (KOA progression): This class comprises 270 participants (KL 0 or 1) who were heathy during the first 12 months (with no incident at the baseline and the first visit) and then they had an incident (KL \(\geq\) 2) recorded at their second visit (24 months) or later until the end of the OAI study. Class D2 (non-KOA): This class involves 270 healthy participants with KL0 or 1 at baseline with no further incidents in both of their knees until the end of the OAI data collection. Output: Classification outputs 0 and 1 corresponding to assignments to classes D1 and D2, respectively. * Dataset E (FSS): Progressors vs. non-progressors using data from the baseline visit along with progression data within the first 24 months  
Input: Dataset E contains 999 features combining datasets A and C. This set of features consists of baseline data \(x_{i,j}^{0},\ j=1,\ldots,724)\) as well as progression data \((dx_{i,j}^{2},\ j=1,\ldots,275)\) within the first 24 months. Similarly, participants were divided into two equal categories (Figure 5), as follows: Class E1 (KOA progression): This class comprises 248 participants who were healthy (KL 0 or 1) in the first 24 months, but they had a KOA incident (KL \(\geq\) 2) at the third visit (36 months) or later until the end of the OAI study in at least one of the two knees or in both. Figure 4: Flow chart of study design for dataset D.  
Class E2 (non-KOA): This class involves 248 healthy participants (KL0 or 1) with no further progression of KOA in both of their knees until the end of the OAI study. Output: Classification outputs 0 and 1 corresponding to assignments to classes E1 and E2, respectively.