AIMC Topic: Longitudinal Studies

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Targeted use of growth mixture modeling: a learning perspective.

Statistics in medicine Nov 2, 2016
From the statistical learning perspective, this paper shows a new direction for the use of growth mixture modeling (GMM), a method of identifying latent subpopulations that manifest heterogeneous outcome trajectories. In the proposed approach, we uti...
Bipolar Disorder Longitudinal Studies Models, Statistical Supervised Machine Learning Patient Outcome Assessment Humans Machine Learning Prognosis Reproducibility of Results
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Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

Annals of the New York Academy of Sciences Sep 14, 2016
Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuo...
Kinetics Models, Biological Quality Assurance, Health Care Radiosurgery Empirical Research Neoplasms Computational Biology Longitudinal Studies Regression Analysis Bayes Theorem In Vivo Dosimetry Humans Neural Networks, Computer Machine Learning Forecasting Databases, Factual Reproducibility of Results
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Making use of longitudinal information in pattern recognition.

Human brain mapping Jul 25, 2016
Longitudinal designs are widely used in medical studies as a means of observing within-subject changes over time in groups of subjects, thereby aiming to improve sensitivity for detecting disease effects. Paralleling an increased use of such studies ...
Humans Prospective Studies Brain Aged Aged, 80 and over Image Interpretation, Computer-Assisted Linear Models Pattern Recognition, Automated Neuroimaging Support Vector Machine Longitudinal Studies Follow-Up Studies Magnetic Resonance Imaging Principal Component Analysis Sensitivity and Specificity Cross-Sectional Studies Middle Aged Cognitive Dysfunction Dementia
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Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

Neurobiology of aging Jul 15, 2016
Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies,...
Disease Progression Severity of Illness Index Longitudinal Studies Regression Analysis Predictive Value of Tests Brain Female Aged Aged, 80 and over Male Alzheimer Disease Datasets as Topic Linear Models Neuroimaging Diffusion Magnetic Resonance Imaging Humans Machine Learning
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Cognitive Test Scores in UK Biobank: Data Reduction in 480,416 Participants and Longitudinal Stability in 20,346 Participants.

PloS one Apr 25, 2016
UK Biobank includes 502,649 middle- and older-aged adults from the general population who have undergone detailed phenotypic assessment. The majority of participants completed tests of cognitive functioning, and on average four years later a sub-grou...
Biological Specimen Banks United Kingdom Cognition Disorders Multifactor Dimensionality Reduction Psychological Tests Male Middle Aged Cognition Longitudinal Studies Principal Component Analysis Humans Female Aged Adult
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Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

IEEE transactions on bio-medical engineering Apr 13, 2016
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-s...
Sensitivity and Specificity Aging Cognitive Dysfunction Longitudinal Studies Magnetic Resonance Imaging Alzheimer Disease Image Interpretation, Computer-Assisted Subtraction Technique Humans Machine Learning Algorithms Brain Reproducibility of Results
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High-Performance Personalized Heartbeat Classification Model for Long-Term ECG Signal.

IEEE transactions on bio-medical engineering Mar 8, 2016
Long-term electrocardiogram (ECG) has become one of the important diagnostic assist methods in clinical cardiovascular domain. Long-term ECG is primarily used for the detection of various cardiovascular diseases that are caused by various cardiac arr...
Patient-Centered Care Electrocardiography, Ambulatory Heart Rate Pattern Recognition, Automated Heart Rate Determination Humans Neural Networks, Computer Algorithms Female Reproducibility of Results Sensitivity and Specificity Male Diagnosis, Computer-Assisted Longitudinal Studies
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Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study.

The American journal of psychiatry Feb 26, 2016
OBJECTIVE: Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a ...
Humans Algorithms Brain Female Aged Young Adult Adult Male Gray Matter Support Vector Machine Longitudinal Studies Magnetic Resonance Imaging Models, Biological Schizophrenia Aging Middle Aged Disease Progression Case-Control Studies Adolescent
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A class of joint models for multivariate longitudinal measurements and a binary event.

Biometrics Jan 11, 2016
Predicting binary events such as newborns with large birthweight is important for obstetricians in their attempt to reduce both maternal and fetal morbidity and mortality. Such predictions have been a challenge in obstetric practice, where longitudin...
Monte Carlo Method Norway Models, Statistical Bayes Theorem Markov Chains Infant, Low Birth Weight Gestational Age Infant, Newborn Sweden Ultrasonography Pregnancy Outcome Longitudinal Studies Humans Machine Learning Pregnancy Female
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Differentiation between treatment-related changes and progressive disease in patients with high grade brain tumors using support vector machine classification based on DCE MRI.

Journal of neuro-oncology Jan 11, 2016
Differentiation between treatment-related changes and progressive disease (PD) remains a major clinical challenge in the follow-up of patients with high grade brain tumors. The aim of this study was to differentiate between treatment-related changes ...
Disease Progression Support Vector Machine Longitudinal Studies Contrast Media Magnetic Resonance Imaging Adult Survival Rate Brain Neoplasms Male Middle Aged Tissue Distribution Glioblastoma Neoplasm Grading Combined Modality Therapy Tumor Burden Image Interpretation, Computer-Assisted Humans Prognosis Female Aged Young Adult
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