Machine learning techniques for personalised medicine approaches in immune-mediated chronic inflammatory diseases: applications and challenges

J Peng, EC Jury, P Dönnes, C Ciurtin - Frontiers in pharmacology, 2021 - frontiersin.org
In the past decade, the emergence of machine learning (ML) applications has led to
significant advances towards implementation of personalised medicine approaches for …

Machine learning (ML) in medicine: Review, applications, and challenges

AM Rahmani, E Yousefpoor, MS Yousefpoor… - Mathematics, 2021 - mdpi.com
Today, artificial intelligence (AI) and machine learning (ML) have dramatically advanced in
various industries, especially medicine. AI describes computational programs that mimic and …

Extensive review on the role of machine learning for multifactorial genetic disorders prediction

DD Solomon, Sonia, K Kumar, K Kanwar, S Iyer… - … Methods in Engineering, 2024 - Springer
The culture of employing machine learning driven assistance and decision making is
currently adopted by a variety of industries. Artificial intelligence encompasses a wide range …

[HTML][HTML] Machine learning application in autoimmune diseases: State of art and future prospectives

MG Danieli, S Brunetto, L Gammeri, D Palmeri… - Autoimmunity …, 2024 - Elsevier
Autoimmune diseases are a group of disorders resulting from an alteration of immune
tolerance, characterized by the formation of autoantibodies and the consequent …

An introduction to machine learning and analysis of its use in rheumatic diseases

KM Kingsmore, CE Puglisi, AC Grammer… - Nature Reviews …, 2021 - nature.com
Abstract Machine learning (ML) is a computerized analytical technique that is being
increasingly employed in biomedicine. ML often provides an advantage over explicitly …

The second decade of anti-TNF-a therapy in clinical practice: New lessons and future directions in the COVID-19 era

G Evangelatos, G Bamias, GD Kitas, G Kollias… - Rheumatology …, 2022 - Springer
Since the late 1990s, tumor necrosis factor alpha (TNF-α) inhibitors (anti-TNFs) have
revolutionized the therapy of immune-mediated inflammatory diseases (IMIDs) affecting the …

Artificial intelligence in rheumatoid arthritis: current status and future perspectives: a state-of-the-art review

S Momtazmanesh, A Nowroozi, N Rezaei - Rheumatology and Therapy, 2022 - Springer
Investigation of the potential applications of artificial intelligence (AI), including machine
learning (ML) and deep learning (DL) techniques, is an exponentially growing field in …

Mechanisms underlying DMARD inefficacy in difficult-to-treat rheumatoid arthritis: a narrative review with systematic literature search

NMT Roodenrijs, PMJ Welsing, J van Roon… - …, 2022 - academic.oup.com
Management of RA patients has significantly improved over the past decades. However, a
substantial proportion of patients is difficult-to-treat (D2T), remaining symptomatic after …

Toward overcoming treatment failure in rheumatoid arthritis

Z Wang, J Huang, D Xie, D He, A Lu… - Frontiers in …, 2021 - frontiersin.org
Rheumatoid arthritis (RA) is an autoimmune disorder characterized by inflammation and
bone erosion. The exact mechanism of RA is still unknown, but various immune cytokines …

Difficult-to-treat rheumatoid arthritis: Current concept and unsolved problems

R Watanabe, T Okano, T Gon, N Yoshida… - Frontiers in …, 2022 - frontiersin.org
Over the past several decades, the treatment of rheumatoid arthritis (RA) has advanced
significantly, and clinical, structural, and functional remission are achievable therapeutic …