: Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario.

Application of Machine Learning Models in Systemic Lupus Erythematosus / Ceccarelli, Fulvia; Natalucci, Francesco; Picciariello, Licia; Ciancarella, Claudia; Dolcini, Giulio; Gattamelata, Angelica; Alessandri, Cristiano; Conti, Fabrizio. - In: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. - ISSN 1422-0067. - 24:5(2023). [10.3390/ijms24054514]

Application of Machine Learning Models in Systemic Lupus Erythematosus

Ceccarelli, Fulvia;Natalucci, Francesco;Picciariello, Licia;Ciancarella, Claudia;Dolcini, Giulio;Gattamelata, Angelica;Alessandri, Cristiano;Conti, Fabrizio
2023

Abstract

: Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario.
2023
Systemic Lupus Erythematosus; artificial intelligence; machine learning models
01 Pubblicazione su rivista::01a Articolo in rivista
Application of Machine Learning Models in Systemic Lupus Erythematosus / Ceccarelli, Fulvia; Natalucci, Francesco; Picciariello, Licia; Ciancarella, Claudia; Dolcini, Giulio; Gattamelata, Angelica; Alessandri, Cristiano; Conti, Fabrizio. - In: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES. - ISSN 1422-0067. - 24:5(2023). [10.3390/ijms24054514]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1698316
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