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Review
. 2022 Nov 11:13:966329.
doi: 10.3389/fimmu.2022.966329. eCollection 2022.

Artificial intelligence for precision medicine in autoimmune liver disease

Alessio Gerussi  1   2 , Miki Scaravaglio  1   2 , Laura Cristoferi  1   2   3 , Damiano Verda  4 , Chiara Milani  1   2 , Elisabetta De Bernardi  5 , Davide Ippolito  6 , Rosanna Asselta  7   8 , Pietro Invernizzi  1   2 , Jakob Nikolas Kather  9   10 , Marco Carbone  1   2
Affiliations
Review

Artificial intelligence for precision medicine in autoimmune liver disease

Alessio Gerussi et al. Front Immunol. .

Abstract

Autoimmune liver diseases (AiLDs) are rare autoimmune conditions of the liver and the biliary tree with unknown etiology and limited treatment options. AiLDs are inherently characterized by a high degree of complexity, which poses great challenges in understanding their etiopathogenesis, developing novel biomarkers and risk-stratification tools, and, eventually, generating new drugs. Artificial intelligence (AI) is considered one of the best candidates to support researchers and clinicians in making sense of biological complexity. In this review, we offer a primer on AI and machine learning for clinicians, and discuss recent available literature on its applications in medicine and more specifically how it can help to tackle major unmet needs in AiLDs.

Keywords: autoimmunity; deep learning; digital pathology; genomics; machine learning; population genetics; radiomics; whole-slide digital image analysis.

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Conflict of interest statement

Author DV is employed by Rulex. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Artificial intelligence and its sub-fields.
Figure 2
Figure 2
Healthy individuals with high genetic risk scores for a specific trait have already detectable abnormalities in several blood analytes. Genetic risk scores generated from risk variants for several traits have been associated with levels of plasma analytes (standard blood analytes, and proteomic and metabolic measurements), revealing that a nonnegligible level of dysregulation of these analytes can already be found in healthy subjects with high genetic risk. These approaches could be potentially leveraged for early detection of diseases.
Figure 3
Figure 3
Interceptive medicine. The paradigm shift to study complex chronic immune-mediated traits proposed by the LifeTime Initiative and the SYSCID Consortium.
Figure 4
Figure 4
Future applications of artificial intelligence in the field of autoimmune liver disease.
See this image and copyright information in PMC

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