Machine learning for precision diagnostics of autoimmunity

Early and accurate diagnosis is crucial to prevent disease development and define therapeutic strategies. Due to predominantly unspecific symptoms, diagnosis of autoimmune diseases (AID) is notoriously challenging. Clinical decision support systems (CDSS) are a promising method with the potential to enhance and expedite precise diagnostics by physicians. However, due to the difficulties of integrating and encoding multi-omics data with clinical values, as well as a lack of standardization, such systems are often limited to certain data types. Accordingly, even sophisticated data models fall short when making accurate disease diagnoses and presenting data analyses in a user-friendly form. Therefore, the integration of various data types is not only an opportunity but also a competitive advantage for research and industry. We have developed an integration pipeline to enable the use of machine learning for patient classification based on multi-omics data in combination with clinical values and laboratory results. The application of our framework resulted in up to 96% prediction accuracy of autoimmune diseases with machine learning models. Our results deliver insights into autoimmune disease research and have the potential to be adapted for applications across disease conditions.

Schlagwörter

Fachgebiet (DDC)

600 - Technik, Medizin, angewandte Wissenschaften

Projekt

Veranstaltung

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

Enddatum der Konferenz

Datum der letzten Prüfung

ISBN

ISSN

2045-2322

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Ja

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Gold

Lizenz

Zitation

KRUTA, Jan, Raphael CARAPITO, Marten TRENDELENBURG, Thierry MARTIN, Marta RIZZI, Reinhard E. VOLL, Andrea CAVALLI, Eriberto NATALI, Patrick MEIER, Marc STAWISKI, Johannes MOSBACHER, Annette MOLLET, Aurelia SANTORO, Miriam CAPRI, Enrico GIAMPIERI, Erik SCHKOMMODAU und Enkelejda MIHO, 2024. Machine learning for precision diagnostics of autoimmunity. Scientific Reports. 13 November 2024. Bd. 14, Nr. 1, S. 27848. DOI 10.1038/s41598-024-76093-7. Verfügbar unter: https://doi.org/10.26041/fhnw-11866

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