Through an adequate survey of the history of the disease, Narrative Medicine (NM) aims to allow the definition and implementation of an effective, appropriate, and shared treatment path. In the present study, standard text mining (TM) techniques are applied, as a Latent Dirichlet Allocation (LDA) model for topic modeling is used to characterize narrative medicine texts written on COVID-19. In particular, the focus was mainly on the writings of patients with Post-acute Sequelae of COVID-19, i.e., PASC, as opposed to writings by health professionals and general reflections on COVID-19. The results suggest that the testimonies of PASC patients can be used for identifying shared issues to focus on to be followed and supported appropriately, even from a psychological point of view.
Characterization of Long COVID using text mining on narrative medicine texts
Scarpino I.;Zucco C.;Cannataro M.
2021-01-01
Abstract
Through an adequate survey of the history of the disease, Narrative Medicine (NM) aims to allow the definition and implementation of an effective, appropriate, and shared treatment path. In the present study, standard text mining (TM) techniques are applied, as a Latent Dirichlet Allocation (LDA) model for topic modeling is used to characterize narrative medicine texts written on COVID-19. In particular, the focus was mainly on the writings of patients with Post-acute Sequelae of COVID-19, i.e., PASC, as opposed to writings by health professionals and general reflections on COVID-19. The results suggest that the testimonies of PASC patients can be used for identifying shared issues to focus on to be followed and supported appropriately, even from a psychological point of view.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
