12 documents found, page 1 of 2
Artificial intelligence and statistical methods for stratification and predicti...
Tavazzi, Erica; Longato, Enrico; Vettoretti, Martina; Aidos, Helena; Trescato, Isotta; Roversi, Chiara; Martins, Andreia S.; Castanho, Eduardo N.Background: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by the progressive loss of motor neurons in the brain and spinal cord. The fact that ALS's disease course is highly heterogeneous, and its determinants not fully known, combined with ALS's relatively low prevalence, renders the successful application of artificial intelligence (AI) techniques particularly arduous...
Dynamic Bayesian networks for stratification of disease progression in amyotrop...
Gromicho, Marta; Leão, Tiago; Oliveira Santos, Miguel; Pinto, Susana; Carvalho, Alexandra M.; Madeira, Sara C.; Carvalho, MamedeBackground and purpose Progression rate is quite variable in amyotrophic lateral sclerosis (ALS); thus, tools for profiling disease progression are essential for timely interventions. The objective was to apply dynamic Bayesian networks (DBNs) to establish the influence of clinical and demographic variables on disease progression rate. Methods In all, 664 ALS patients from our database were included stratified ...
Learning prognostic models using a mixture of biclustering and triclustering: p...
Soares, Diogo F.; Henriques, Rui; Gromicho, Marta; Carvalho, Mamede; Madeira, Sara C.Longitudinal cohort studies to study disease progression generally combine temporal features produced under periodic assessments (clinical follow-up) with static features associated with single-time assessments, genetic, psychophysiological, and demographic profiles. Subspace clustering, including biclustering and triclustering stances, enables the discovery of local and discriminative patterns from such multid...
Targeting the uncertainty of predictions at patient-level using an ensemble of ...
Pereira, Telma; Cardoso, Sandra; Guerreiro, Manuela; De Mendonça, Alexandre; Madeira, Sara C.Despite being able to make accurate predictions, most existing prognostic models lack a proper indication about the uncertainty of each prediction, that is, the risk of prediction error for individual patients. This hampers their translation to primary care settings through decision support systems. To address this problem, we studied different methods for transforming classifiers into probabilistic/confidence-...
Spreading in ALS: The relative impact of upper and lower motor neuron involvement
Gromicho, Marta; Figueiral, Manuel; Uysal, Hilmi; Grosskreutz, Julian; Kuzma‐Kozakiewicz, Magdalena; Pinto, Susana; Petri, Susanne; Madeira, Sara C.Objective: To investigate disease spread in amyotrophic lateral sclerosis (ALS), and determine the influence of lower (LMN) and upper motor neuron (UMN) involvement. Methods: We assessed disease spread in ALS in 1376 consecutively studied patients, from five European centers, applying an agreed proforma to assess LMN and UMN signs. We defined the pattern of disease onset and progression from predominant UMN or ...
Neuropsychological predictors of conversion from mild cognitive impairment to A...
Pereira, Telma; Ferreira, Francisco L.; Cardoso, Sandra; Silva, Dina; De Mendonça, Alexandre; Guerreiro, Manuela; Madeira, Sara C.Background: Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are chal...
Neuropsychological predictors of conversion from mild cognitive impairment to A...
Pereira, Telma; Ferreira, Francisco L.; Cardoso, Sandra; Silva, Dina; Mendonça, Alexandre de; Guerreiro, Manuela; Madeira, Sara C.Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are chall...
Predicting progression of mild cognitive impairment to dementia using neuropsyc...
Pereira, Telma; Lemos, Luís; Cardoso, Sandra; Silva, Dina; Rodrigues, Ana; Santana, Isabel; Mendonça, Alexandre de; Guerreiro, Manuela; Madeira, Sara C.Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning...
Prognostic models based on patient snapshots and time windows: predicting disea...
Carreiro, André V.; Amaral, Pedro; Pinto, Susana; Tomás, Pedro; Carvalho, Mamede; Madeira, Sara C.Amyotrophic Lateral Sclerosis (ALS) is a devastating disease and the most common neurodegenerative disorder of young adults. ALS patients present a rapidly progressive motor weakness. This usually leads to death in a few years by respiratory failure. The correct prediction of respiratory insufficiency is thus key for patient management. In this context, we propose an innovative approach for prognostic predictio...
Integrative biomarker discovery in neurodegenerative diseases
Carreiro, André V.; De Mendonça, Alexandre; Carvalho, Mamede; Madeira, Sara C.Data mining has been widely applied in biomarker discovery resulting in significant findings of different clinical and biological biomarkers. With developments in technology, from genomics to proteomics analysis, a deluge of data has become available, as well as standardized data repositories. Nonetheless, researchers are still facing important challenges in analyzing the data, especially when considering the c...