Model Description. The binary classifier aims to detect which patients belong to the high increasing QoL trajectory (positive class) during the 18 month period from baseline. The negative class emerges from the grouping of the low decreasing and moderate QoL trajectory clusters identified during trajectory analysis (D4.3b), as depicted in Fig. I5.
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Model Description. The binary classifier aims to detect which patients belong to the high increasing low decreasing QoL trajectory (positive class) during the 18 month period from baseline. The negative class emerges from the grouping of the low decreasing high increasing and moderate QoL trajectory clusters identified during trajectory analysis (D4.3b), as depicted in Fig. I5I3.
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Sources: Grant Agreement