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Longitudinal Studies

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Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning.

IEEE transactions on medical imaging
The early postnatal period witnesses rapid and dynamic brain development. However, the relationship between brain anatomical structure and cognitive ability is still unknown. Currently, there is no explicit model to characterize this relationship in ...

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BMC geriatrics
BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a ne...

Estrous detection by continuous measurements of vaginal temperature and conductivity with supervised machine learning in cattle.

Theriogenology
This study aimed to evaluate the effectiveness of estrous detection technique based on continuous measurements of vaginal temperature (VT) and conductivity (VC) with supervised machine learning in cattle. The VT and VC of 17 cows in tie-stalls were m...

Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

Journal of biomedical informatics
INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.

Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c.

Journal of biomedical informatics
Accurate and reliable prediction of clinical progression over time has the potential to improve the outcomes of chronic disease. The classical approach to analyzing longitudinal data is to use (generalized) linear mixed-effect models (GLMM). However,...

Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?

Journal of behavioral medicine
Behavioral weight loss (WL) trials show that, on average, participants regain lost weight unless provided long-term, intensive-and thus costly-intervention. Optimization solutions have shown mixed success. The artificial intelligence principle of "re...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...

Applying artificial intelligence to assess the impact of orthognathic treatment on facial attractiveness and estimated age.

International journal of oral and maxillofacial surgery
This observational study aimed to use artificial intelligence to describe the impact of orthognathic treatment on facial attractiveness and age appearance. Pre- and post-treatment photographs (n=2164) of 146 consecutive orthognathic patients were col...

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatmen...

Unsupervised Machine Learning to Identify High Likelihood of Dementia in Population-Based Surveys: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Dementia is increasing in prevalence worldwide, yet frequently remains undiagnosed, especially in low- and middle-income countries. Population-based surveys represent an underinvestigated source to identify individuals at risk of dementia...