A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases

IS Stafford, M Kellermann, E Mossotto, RM Beattie… - NPJ digital …, 2020‏ - nature.com
Autoimmune diseases are chronic, multifactorial conditions. Through machine learning (ML),
a branch of the wider field of artificial intelligence, it is possible to extract patterns within …

A comprehensive literatures update of clinical researches of superparamagnetic resonance iron oxide nanoparticles for magnetic resonance imaging

YXJ Wáng, JM Idée - Quantitative imaging in medicine and …, 2017‏ - pmc.ncbi.nlm.nih.gov
This paper aims to update the clinical researches using superparamagnetic iron oxide
(SPIO) nanoparticles as magnetic resonance imaging (MRI) contrast agent published during …

Machine learning assisted-nanomedicine using magnetic nanoparticles for central nervous system diseases

A Tomitaka, A Vashist, N Kolishetti, M Nair - Nanoscale Advances, 2023‏ - pubs.rsc.org
Magnetic nanoparticles possess unique properties distinct from other types of nanoparticles
developed for biomedical applications. Their unique magnetic properties and …

Application of artificial intelligence in pharmaceutical and biomedical studies

A Thakur, AP Mishra, B Panda… - Current …, 2020‏ - benthamdirect.com
Background: Artificial intelligence (AI) is the way to model human intelligence to accomplish
certain tasks without much intervention of human beings. The term AI was first used in 1956 …

Iron oxide as an MRI contrast agent for cell tracking: supplementary issue

DJ Korchinski, M Taha, R Yang… - Magnetic resonance …, 2015‏ - journals.sagepub.com
Iron oxide contrast agents have been combined with magnetic resonance imaging for cell
tracking. In this review, we discuss coating properties and provide an overview of ex vivo …

Current review and next steps for artificial intelligence in multiple sclerosis risk research

M Hartmann, N Fenton, R Dobson - Computers in Biology and Medicine, 2021‏ - Elsevier
In the last few decades, the prevalence of multiple sclerosis (MS), a chronic inflammatory
disease of the nervous system, has increased, particularly in Northern European countries …

[HTML][HTML] A systematic review of the application of machine-learning algorithms in multiple sclerosis

M Vázquez-Marrufo, E Sarrias-Arrabal… - Neurología (English …, 2023‏ - Elsevier
Introduction The applications of artificial intelligence, and in particular automatic learning or
“machine learning”(ML), constitute both a challenge and a great opportunity in numerous …

Dimensional neuroimaging endophenotypes: neurobiological representations of disease heterogeneity through machine learning

J Wen, M Antoniades, Z Yang, G Hwang… - Biological …, 2024‏ - Elsevier
Abstract Machine learning has been increasingly used to obtain individualized
neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in …

[HTML][HTML] The role of advanced magnetic resonance imaging techniques in multiple sclerosis clinical trials

KR Mahajan, D Ontaneda - Neurotherapeutics, 2017‏ - Elsevier
Magnetic resonance imaging has been crucial in the development of anti-inflammatory
disease-modifying treatments. The current landscape of multiple sclerosis clinical trials is …

Recent advances in development of nanomedicines for multiple sclerosis diagnosis

Q Zhang, X Dai, H Zhang, Y Zeng, K Luo… - Biomedical …, 2021‏ - iopscience.iop.org
Multiple sclerosis (MS) is a neurodegenerative disease with a high morbidity and disease
burden. It is characterized by the loss of the myelin sheath, resulting in the disruption of …