Cargando…

The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review

BACKGROUND: Multiple sclerosis (MS) is a neurological condition whose symptoms, severity, and progression over time vary enormously among individuals. Ideally, each person living with MS should be provided with an accurate prognosis at the time of diagnosis, precision in initial and subsequent treat...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hossain, Md Zakir, Daskalaki, Elena, Brüstle, Anne, Desborough, Jane, Lueck, Christian J., Suominen, Hanna
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476596/ https://www.ncbi.nlm.nih.gov/pubmed/36109726 http://dx.doi.org/10.1186/s12911-022-01985-5

Ejemplares similares

Personalizing Medicine and Technologies to Address the Experiences and Needs of People with Multiple Sclerosis
por: Henschke, Adam, et al.
Publicado: (2021)

Integrating Multiple Inputs Into an Artificial Pancreas System: Narrative Literature Review
por: Hettiarachchi, Chirath, et al.
Publicado: (2022)

‘It struck at the heart of who I thought I was’: A meta‐synthesis of the qualitative literature examining the experiences of people with multiple sclerosis
por: Desborough, Jane, et al.
Publicado: (2020)

The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey
por: Daskalaki, Elena, et al.
Publicado: (2022)

‘They're getting a taste of our world’: A qualitative study of people with multiple sclerosis' experiences of accessing health care during the COVID‐19 pandemic in the Australian Capital Territory
por: Parkinson, Anne, et al.
Publicado: (2021)

Machine Learning Approaches in Study of Multiple Sclerosis Disease Through Magnetic Resonance Images
por: Moazami, Faezeh, et al.
Publicado: (2021)

Understanding Magnetic Resonance Imaging in Multiple Sclerosis (UMIMS): Development and Piloting of an Online Education Program About Magnetic Resonance Imaging for People With Multiple Sclerosis
por: Freund, Magalie, et al.
Publicado: (2022)

The Emerging Role of Neutrophil Granulocytes in Multiple Sclerosis
por: Woodberry, Tonia, et al.
Publicado: (2018)

Multiple Sclerosis Lesions Segmentation in Magnetic Resonance Imaging using Ensemble Support Vector Machine (ESVM)
por: HosseiniPanah, S., et al.
Publicado: (2019)

Continuous evolution of magnetic resonance imaging in multiple sclerosis
por: Tallantyre, E. C., et al.
Publicado: (2016)

Machine learning to analyse omic-data for COVID-19 diagnosis and prognosis
por: Liu, Xuehan, et al.
Publicado: (2023)

Machine learning for detecting DNA attachment on SPR biosensor
por: Mondal, Himadri Shekhar, et al.
Publicado: (2023)

Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features
por: Ion-Mărgineanu, Adrian, et al.
Publicado: (2017)

Which features of postural sway are effective in distinguishing Parkinson's disease from controls? A systematic review
por: Ge, Wenbo, et al.
Publicado: (2020)

Quantitative Magnetic Resonance Imaging of Cortical Multiple Sclerosis Pathology
por: Tardif, Christine L., et al.
Publicado: (2012)

Estimation of Multiple Sclerosis lesion age on magnetic resonance imaging
por: Sweeney, Elizabeth M., et al.
Publicado: (2020)

Honing in on magnetic resonance imaging predictors of multiple sclerosis pathology
por: Schmierer, Klaus
Publicado: (2023)

A user preference analysis of commercial breath ketone sensors to inform the development of portable breath ketone sensors for diabetes management in young people
por: Brew-Sam, Nicola, et al.
Publicado: (2022)

Applicability of McDonald 2010 and Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) 2016 Magnetic Resonance Imaging Criteria for the Diagnosis of Multiple Sclerosis in Sri Lanka
por: Gamage, Sujani Madhurika Kodagoda, et al.
Publicado: (2018)

Magnetic resonance markers of tissue damage related to connectivity disruption in multiple sclerosis
por: Solana, Elisabeth, et al.
Publicado: (2018)

Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis
por: Mani, Ashika, et al.
Publicado: (2021)

The current understanding of precision medicine and personalised medicine in selected research disciplines: study protocol of a systematic concept analysis
por: Brew-Sam, Nicola, et al.
Publicado: (2022)

Intertwined like a double helix: A meta‐synthesis of the qualitative literature examining the experiences of living with someone with multiple sclerosis
por: Parkinson, Anne, et al.
Publicado: (2022)

Application of Texture Analysis in Diagnosis of Multiple Sclerosis by Magnetic Resonance Imaging
por: Ardakani, Ali Abbasian, et al.
Publicado: (2015)

Longitudinal Magnetic Resonance Imaging of Cerebral Microbleeds in Multiple Sclerosis Patients
por: Subramanian, Karthikeyan, et al.
Publicado: (2020)

Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines
por: Filippi, Massimo, et al.
Publicado: (2019)

Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis
por: Granziera, Cristina, et al.
Publicado: (2021)

Magnetic Resonance Imaging in Primary Progressive Multiple Sclerosis Patients: Review
por: Siger, Malgorzata
Publicado: (2022)

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes
por: Daskalaki, Elena, et al.
Publicado: (2016)

IMPACT OF AEROBIC EXERCISE ON CLINICAL AND MAGNETIC RESONANCE IMAGING BIOMARKERS IN PERSONS WITH MULTIPLE SCLEROSIS: AN EXPLORATORY RANDOMIZED CONTROLLED TRIAL
por: SAVŠEK, Lina, et al.
Publicado: (2021)

Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques
por: Taloni, Alessandro, et al.
Publicado: (2022)

Objective perimetry and progression of multiple sclerosis
por: Maddess, Ted, et al.
Publicado: (2022)

Magnetic resonance imaging biomarkers for the early diagnosis of Alzheimer's disease: a machine learning approach
por: Salvatore, Christian, et al.
Publicado: (2015)

Magnetic Resonance Imaging in Multiple Sclerosis – Patients' Experiences, Information Interests and Responses to an Education Programme
por: Brand, Judith, et al.
Publicado: (2014)

7 Tesla Magnetic Resonance Imaging to Detect Cortical Pathology in Multiple Sclerosis
por: Yao, Bing, et al.
Publicado: (2014)

Magnetic resonance diffusion tensor imaging for occult lesion detection in multiple sclerosis
por: Chen, Jiafeng, et al.
Publicado: (2017)

White Matter Evaluation in Multiple Sclerosis Through Magnetic Resonance Kurtosis Imaging
por: Sahin, Sevim, et al.
Publicado: (2019)

New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis
por: Ineichen, Benjamin V., et al.
Publicado: (2021)

Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions
por: Arnold, T. Campbell, et al.
Publicado: (2022)

Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images
por: Khastavaneh, H., et al.
Publicado: (2017)

Cannot write session to /tmp/vufind_sessions/sess_06d2qfqefgqgbujdb57o71eeuk