AIMC Topic: Longitudinal Studies

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Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

JAMA ophthalmology
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.

Predictors of Dementia in the Oldest Old: A Novel Machine Learning Approach.

Alzheimer disease and associated disorders
BACKGROUND: Incidence of dementia increases exponentially with age; little is known about its risk factors in the ninth and 10th decades of life. We identified predictors of dementia with onset after age 85 years in a longitudinal population-based co...

Integrating Convolutional Neural Networks and Multi-Task Dictionary Learning for Cognitive Decline Prediction with Longitudinal Images.

Journal of Alzheimer's disease : JAD
BACKGROUND: Disease progression prediction based on neuroimaging biomarkers is vital in Alzheimer's disease (AD) research. Convolutional neural networks (CNN) have been proved to be powerful for various computer vision research by refining reliable a...

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

Neuro-oncology
BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hype...

Detection of Flares by Decrease in Physical Activity, Collected Using Wearable Activity Trackers in Rheumatoid Arthritis or Axial Spondyloarthritis: An Application of Machine Learning Analyses in Rheumatology.

Arthritis care & research
OBJECTIVE: Flares in rheumatoid arthritis (RA) and axial spondyloarthritis (SpA) may influence physical activity. The aim of this study was to assess longitudinally the association between patient-reported flares and activity-tracker-provided steps p...

Automatic and Continuous Discomfort Detection for Premature Infants in a NICU Using Video-Based Motion Analysis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Frequent pain and discomfort in premature infants can lead to long-term adverse neurodevelopmental outcomes. Video-based monitoring is considered to be a promising contactless method for identification of discomfort moments. In this study, we propose...

An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures.

Journal of psychiatry & neuroscience : JPN
BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conver...

Rhythmic robotic training enhances motor skills of both rhythmic and discrete upper-limb movements after stroke: a longitudinal pilot study.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
Discrete and rhythmic movements are two fundamental motor primitives being, at least partially, controlled by separate neural circuitries. After a stroke, both primitives may be impaired in the upper limb. Currently, intensive functional movement the...

Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD
BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learning (ML) algorithms are specifically designed for the purpose of prediction; however. identifying opti...