[HTML][HTML] Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review
Abstract Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative
disorder characterised by the progressive loss of motor neurons in the brain and spinal cord …
disorder characterised by the progressive loss of motor neurons in the brain and spinal cord …
Biclustering data analysis: a comprehensive survey
Biclustering, the simultaneous clustering of rows and columns of a data matrix, has proved
its effectiveness in bioinformatics due to its capacity to produce local instead of global …
its effectiveness in bioinformatics due to its capacity to produce local instead of global …
Temporal stratification of amyotrophic lateral sclerosis patients using disease progression patterns
Identifying groups of patients with similar disease progression patterns is key to understand
disease heterogeneity, guide clinical decisions and improve patient care. In this paper, we …
disease heterogeneity, guide clinical decisions and improve patient care. In this paper, we …
Biclustering fMRI time series: a comparative study
Background The effectiveness of biclustering, simultaneous clustering of rows and columns
in a data matrix, was shown in gene expression data analysis. Several researchers …
in a data matrix, was shown in gene expression data analysis. Several researchers …
[HTML][HTML] Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis
Longitudinal cohort studies to study disease progression generally combine temporal
features produced under periodic assessments (clinical follow-up) with static features …
features produced under periodic assessments (clinical follow-up) with static features …
Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis
This work proposes a new class of explainable prognostic models for longitudinal data
classification using triclusters. A new temporally constrained triclustering algorithm, termed …
classification using triclusters. A new temporally constrained triclustering algorithm, termed …
Learning prognostic models using disease progression patterns: Predicting the need for non-invasive ventilation in amyotrophic lateral sclerosis
Amyotrophic Lateral Sclerosis is a devastating neurodegenerative disease causing rapid
degeneration of motor neurons and usually leading to death by respiratory failure. Since …
degeneration of motor neurons and usually leading to death by respiratory failure. Since …
[PDF][PDF] Predicting the functional rating scale and self-assessment status of ALS patients with sensor data
Abstract Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease causing
progressive loss of cognitive and motor functions. Due to limited understanding of its …
progressive loss of cognitive and motor functions. Due to limited understanding of its …
Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis
F Papaiz, MET Dourado Jr… - BMC Medical Informatics …, 2024 - Springer
Abstract Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable
challenge due to patients exhibiting different onset sites, progression rates, and survival …
challenge due to patients exhibiting different onset sites, progression rates, and survival …
[PDF][PDF] Hierarchical Modelling for ALS Prognosis: Predicting the Progression Towards Critical Events.
Abstract Amyotrophic Lateral Sclerosis is a neurodegenerative disease that leads to a
patient's progressive loss of cognitive and motor capacities. Its mechanisms are poorly …
patient's progressive loss of cognitive and motor capacities. Its mechanisms are poorly …