Systemic sclerosis (SSc) is a rare connective tissue disease that can affect different organs and has extremely heterogenous presentations. This complexity makes it difficult to perform an early diagnosis and a subsequent subclassification of the disease. This hinders a personalized approach in clinical practice. In this context, machine learning (ML), a branch of artificial intelligence (AI), is able to recognize relationships in data and predict outcomes.
The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review / Bonomi, Francesco; Peretti, Silvia; Lepri, Gemma; Venerito, Vincenzo; Russo, Edda; Bruni, Cosimo; Iannone, Florenzo; Tangaro, Sabina; Amedei, Amedeo; Guiducci, Serena; Matucci Cerinic, Marco; Bellando Randone, Silvia. - In: JOURNAL OF PERSONALIZED MEDICINE. - ISSN 2075-4426. - ELETTRONICO. - 12:(2022), pp. 1198-1208. [10.3390/jpm12081198]
The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review
Bonomi, Francesco;Peretti, Silvia;Lepri, Gemma;Russo, Edda;Bruni, Cosimo;Amedei, Amedeo;Guiducci, Serena;Matucci Cerinic, Marco;Bellando Randone, Silvia
2022
Abstract
Systemic sclerosis (SSc) is a rare connective tissue disease that can affect different organs and has extremely heterogenous presentations. This complexity makes it difficult to perform an early diagnosis and a subsequent subclassification of the disease. This hinders a personalized approach in clinical practice. In this context, machine learning (ML), a branch of artificial intelligence (AI), is able to recognize relationships in data and predict outcomes.
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