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Table 2 Classification models designed along with their respective encoded output vectors

From: Predicting clinical outcomes of radiotherapy for head and neck squamous cell carcinoma patients using machine learning algorithms

Model number

Model name

Output label

1

Choice of Initial Treatment (the first treatment that was given to the patient, typically surgery or radiotherapy)

Label 1: Surgery

Label 0: Radiation Therapy

2

Residual (disease fails to clear after even three months of completion of radiotherapy; this parameter does not apply to patients who underwent initial surgery)

Label 1: Residual present

Label 0: Residual Absent

3

Locoregional recurrence (disease recurs in the irradiated site itself sometime after completion of treatment)

Label 1: Locoregional Recurrence

Label 0: No Locoregional Recurrence

4

Distant recurrence (the recurrence of the disease at a site away from its origin, typically by spreading through the blood)

Label 1: Distant Recurrence present

Label 0- No Distant Recurrence

5

New Primary (new cancer, unrelated to the treated cancer, developing in the head and neck region)

Label 1: New Primary present

Label 0: New Primary absent