AIMC Topic: Longitudinal Studies
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Association of a Serum Protein Signature With Rheumatoid Arthritis Development.
Arthritis & rheumatology (Hoboken, N.J.)
Nov 10, 2020
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...
Adolescent
Arthritis, Rheumatoid
Proteomics
Indians, North American
Adult
Male
Middle Aged
Disease Progression
Humans
Asymptomatic Diseases
Lectins
Calreticulin
Toll-Like Receptor 2
Female
Ficolins
Aged
Young Adult
Machine Learning
Tumor Necrosis Factor-alpha
Longitudinal Studies
Anti-Citrullinated Protein Antibodies
Interleukin-1
Rheumatoid Factor
Effects of Robotic Exoskeleton-Aided Gait Training in the Strength, Body Balance, and Walking Speed in Individuals With Multiple Sclerosis: A Single-Group Preliminary Study.
Archives of physical medicine and rehabilitation
Nov 9, 2020
OBJECTIVE: To assess effects of 15 exoskeleton-assisted gait training sessions, reflected by the muscle strength of the lower limbs and by walking speed immediately after the training sessions and at the 6-week follow-up.
Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar.
BMJ (Clinical research ed.)
Nov 4, 2020
OBJECTIVE: To assess the consistency of machine learning and statistical techniques in predicting individual level and population level risks of cardiovascular disease and the effects of censoring on risk predictions.
Assessment of Facial Morphologic Features in Patients With Congenital Adrenal Hyperplasia Using Deep Learning.
JAMA network open
Nov 2, 2020
IMPORTANCE: Congenital adrenal hyperplasia (CAH) is the most common primary adrenal insufficiency in children, involving excess androgens secondary to disrupted steroidogenesis as early as the seventh gestational week of life. Although structural bra...
Elastic Registration-driven Deep Learning for Longitudinal Assessment of Systemic Sclerosis Interstitial Lung Disease at CT.
Radiology
Oct 20, 2020
Background Longitudinal follow-up of interstitial lung diseases (ILDs) at CT mainly relies on the evaluation of the extent of ILD, without accounting for lung shrinkage. Purpose To develop a deep learning-based method to depict worsening of ILD based...
Effects of nerve-sparing procedures on bowel function after robot-assisted radical prostatectomy: A longitudinal study.
The international journal of medical robotics + computer assisted surgery : MRCAS
Oct 8, 2020
BACKGROUND: This study aimed to evaluate rectal pain and bowel function of the patients following robot-assisted radical prostatectomy (RARP).
Predicting the progression of mild cognitive impairment to Alzheimer's disease by longitudinal magnetic resonance imaging-based dictionary learning.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Aug 14, 2020
OBJECTIVE: Efficient prediction of the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) is important for the early intervention and management of AD. The aim of our study was to develop a longitudinal structural magnetic res...
Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.
Journal of medical Internet research
Aug 12, 2020
BACKGROUND: Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tw...
Predicting Alzheimer's disease progression using deep recurrent neural networks.
NeuroImage
Aug 4, 2020
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. In this study, given multimodal AD markers and clinical diagnosis of an individual from one or more t...
Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies.
Proceedings of the National Academy of Sciences of the United States of America
Jul 27, 2020
Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., ...
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