Prediction of disease progression and outcomes in multiple sclerosis with machine learning
MF Pinto, H Oliveira, S Batista, L Cruz, M Pinto… - Scientific reports, 2020 - nature.com
Multiple Sclerosis is a chronic inflammatory disease, affecting the Central Nervous System
and leading to irreversible neurological damage, such as long term functional impairment …
and leading to irreversible neurological damage, such as long term functional impairment …
An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis
Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This
neurological disorder damages nerve cell sheaths, with treatments focusing on symptom …
neurological disorder damages nerve cell sheaths, with treatments focusing on symptom …
Current review and next steps for artificial intelligence in multiple sclerosis risk research
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 …
disease of the nervous system, has increased, particularly in Northern European countries …
Multi-dimensional classification via kNN feature augmentation
In multi-dimensional classification (MDC), each training example is represented by a single
instance (feature vector) while associated with multiple class variables, each of which …
instance (feature vector) while associated with multiple class variables, each of which …
Multi-dimensional Bayesian network classifiers: A survey
Multi-dimensional classification is a cutting-edge problem, in which the values of multiple
class variables have to be simultaneously assigned to a given example. It is an extension of …
class variables have to be simultaneously assigned to a given example. It is an extension of …
Multi-dimensional classification via selective feature augmentation
In multi-dimensional classification (MDC), the semantics of objects are characterized by
multiple class spaces from different dimensions. Most MDC approaches try to explicitly …
multiple class spaces from different dimensions. Most MDC approaches try to explicitly …
Review of advanced computational approaches on multiple sclerosis segmentation and classification
M Shanmuganathan, S Almutairi… - IET Signal …, 2020 - Wiley Online Library
In this study, a survey of multiple sclerosis (MS) classification and segmentation process is
presented, which is based on magnetic resonance imaging. Knowledge of MS lesions is …
presented, which is based on magnetic resonance imaging. Knowledge of MS lesions is …
Multi-dimensional classification via decomposed label encoding
In multi-dimensional classification (MDC), a number of class variables are assumed in the
output space with each of them specifying the class membership wrt one heterogeneous …
output space with each of them specifying the class membership wrt one heterogeneous …
Multi-dimensional classification via sparse label encoding
In multi-dimensional classification (MDC), there are multiple class variables in the output
space with each of them corresponding to one heterogeneous class space. Due to the …
space with each of them corresponding to one heterogeneous class space. Due to the …
Multi-dimensional classification via stacked dependency exploitation
Multi-dimensional classification (MDC) aims to build classification models for multiple
heterogenous class spaces simultaneously, where each class space characterizes the …
heterogenous class spaces simultaneously, where each class space characterizes the …