Literature DB >> 34658859

Machine Learning Techniques for Personalised Medicine Approaches in Immune-Mediated Chronic Inflammatory Diseases: Applications and Challenges.

Junjie Peng1, Elizabeth C Jury1,2, Pierre Dönnes3, Coziana Ciurtin1.   

Abstract

In the past decade, the emergence of machine learning (ML) applications has led to significant advances towards implementation of personalised medicine approaches for improved health care, due to the exceptional performance of ML models when utilising complex big data. The immune-mediated chronic inflammatory diseases are a group of complex disorders associated with dysregulated immune responses resulting in inflammation affecting various organs and systems. The heterogeneous nature of these diseases poses great challenges for tailored disease management and addressing unmet patient needs. Applying novel ML techniques to the clinical study of chronic inflammatory diseases shows promising results and great potential for precision medicine applications in clinical research and practice. In this review, we highlight the clinical applications of various ML techniques for prediction, diagnosis and prognosis of autoimmune rheumatic diseases, inflammatory bowel disease, autoimmune chronic kidney disease, and multiple sclerosis, as well as ML applications for patient stratification and treatment selection. We highlight the use of ML in drug development, including target identification, validation and drug repurposing, as well as challenges related to data interpretation and validation, and ethical concerns related to the use of artificial intelligence in clinical research.
Copyright © 2021 Peng, Jury, Dönnes and Ciurtin.

Entities:  

Keywords:  autoimmune disease; biomarker; machine learning; omics; personalised medicine

Year:  2021        PMID: 34658859      PMCID: PMC8514674          DOI: 10.3389/fphar.2021.720694

Source DB:  PubMed          Journal:  Front Pharmacol        ISSN: 1663-9812            Impact factor:   5.810


  91 in total

1.  Implementation of a Pipeline Using Disease-Disease Associations for Computational Drug Repurposing.

Authors:  Preethi Balasundaram; Rohini Kanagavelu; Nivya James; Sayoni Maiti; Shanthi Veerappapillai; Ramanathan Karuppaswamy
Journal:  Methods Mol Biol       Date:  2019

Review 2.  Applications of machine learning in drug discovery and development.

Authors:  Jessica Vamathevan; Dominic Clark; Paul Czodrowski; Ian Dunham; Edgardo Ferran; George Lee; Bin Li; Anant Madabhushi; Parantu Shah; Michaela Spitzer; Shanrong Zhao
Journal:  Nat Rev Drug Discov       Date:  2019-06       Impact factor: 84.694

3.  Identification of a Rule to Predict Response to Sarilumab in Patients with Rheumatoid Arthritis Using Machine Learning and Clinical Trial Data.

Authors:  Markus Rehberg; Clemens Giegerich; Amy Praestgaard; Hubert van Hoogstraten; Melitza Iglesias-Rodriguez; Jeffrey R Curtis; Jacques-Eric Gottenberg; Andreas Schwarting; Santos Castañeda; Andrea Rubbert-Roth; Ernest H S Choy
Journal:  Rheumatol Ther       Date:  2021-09-14

4.  Machine Learning Improves Cardiovascular Risk Definition for Young, Asymptomatic Individuals.

Authors:  Fátima Sánchez-Cabo; Xavier Rossello; Valentín Fuster; Fernando Benito; Jose Pedro Manzano; Juan Carlos Silla; Juan Miguel Fernández-Alvira; Belén Oliva; Leticia Fernández-Friera; Beatriz López-Melgar; José María Mendiguren; Javier Sanz; Jose María Ordovás; Vicente Andrés; Antonio Fernández-Ortiz; Héctor Bueno; Borja Ibáñez; José Manuel García-Ruiz; Enrique Lara-Pezzi
Journal:  J Am Coll Cardiol       Date:  2020-10-06       Impact factor: 24.094

5.  Classification of Paediatric Inflammatory Bowel Disease using Machine Learning.

Authors:  E Mossotto; J J Ashton; T Coelho; R M Beattie; B D MacArthur; S Ennis
Journal:  Sci Rep       Date:  2017-05-25       Impact factor: 4.379

6.  Mechanism of baricitinib supports artificial intelligence-predicted testing in COVID-19 patients.

Authors:  Justin Stebbing; Venkatesh Krishnan; Anabela Cardoso; Mario Corbellino; Stephanie de Bono; Silvia Ottaviani; Giacomo Casalini; Peter J Richardson; Vanessa Monteil; Volker M Lauschke; Ali Mirazimi; Sonia Youhanna; Yee-Joo Tan; Fausto Baldanti; Antonella Sarasini; Jorge A Ross Terres; Brian J Nickoloff; Richard E Higgs; Guilherme Rocha; Nicole L Byers; Douglas E Schlichting; Ajay Nirula
Journal:  EMBO Mol Med       Date:  2020-06-24       Impact factor: 12.137

7.  Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases.

Authors:  Yury E Glazyrin; Dmitry V Veprintsev; Irina A Ler; Maria L Rossovskaya; Svetlana A Varygina; Sofia L Glizer; Tatiana N Zamay; Marina M Petrova; Zoran Minic; Maxim V Berezovski; Anna S Kichkailo
Journal:  Int J Mol Sci       Date:  2020-07-07       Impact factor: 5.923

8.  Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission.

Authors:  Xintian Xu; Ping Chen; Jingfang Wang; Jiannan Feng; Hui Zhou; Xuan Li; Wu Zhong; Pei Hao
Journal:  Sci China Life Sci       Date:  2020-01-21       Impact factor: 6.038

Review 9.  Machine learning applications in drug development.

Authors:  Clémence Réda; Emilie Kaufmann; Andrée Delahaye-Duriez
Journal:  Comput Struct Biotechnol J       Date:  2019-12-26       Impact factor: 7.271

10.  Target identification among known drugs by deep learning from heterogeneous networks.

Authors:  Xiangxiang Zeng; Siyi Zhu; Weiqiang Lu; Zehui Liu; Jin Huang; Yadi Zhou; Jiansong Fang; Yin Huang; Huimin Guo; Lang Li; Bruce D Trapp; Ruth Nussinov; Charis Eng; Joseph Loscalzo; Feixiong Cheng
Journal:  Chem Sci       Date:  2020-01-13       Impact factor: 9.969

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  6 in total

Review 1.  Tailored treatment strategies and future directions in systemic lupus erythematosus.

Authors:  Dionysis Nikolopoulos; Lampros Fotis; Ourania Gioti; Antonis Fanouriakis
Journal:  Rheumatol Int       Date:  2022-04-21       Impact factor: 3.580

Review 2.  Immunoglobulin G N-glycan Biomarkers for Autoimmune Diseases: Current State and a Glycoinformatics Perspective.

Authors:  Konstantinos Flevaris; Cleo Kontoravdi
Journal:  Int J Mol Sci       Date:  2022-05-06       Impact factor: 6.208

3.  Identification and Prediction of Chronic Diseases Using Machine Learning Approach.

Authors:  Rayan Alanazi
Journal:  J Healthc Eng       Date:  2022-02-25       Impact factor: 2.682

4.  Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

Authors:  Dongjie Chen; Jixing Liu; Longjun Zang; Tijun Xiao; Xianlin Zhang; Zheng Li; Hongwei Zhu; Wenzhe Gao; Xiao Yu
Journal:  Int J Biol Sci       Date:  2022-01-01       Impact factor: 6.580

5.  Non-destructive characterization of bone mineral content by machine learning-assisted electrochemical impedance spectroscopy.

Authors:  Aihik Banerjee; Youyi Tai; Nosang V Myung; Jin Nam
Journal:  Front Bioeng Biotechnol       Date:  2022-09-05

Review 6.  CD8+ T Cell Phenotype and Function in Childhood and Adult-Onset Connective Tissue Disease.

Authors:  Anna Radziszewska; Zachary Moulder; Elizabeth C Jury; Coziana Ciurtin
Journal:  Int J Mol Sci       Date:  2022-09-28       Impact factor: 6.208

  6 in total

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