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Disease Progression

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A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease.

NeuroImage
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to pr...

Training recurrent neural networks robust to incomplete data: Application to Alzheimer's disease progression modeling.

Medical image analysis
Disease progression modeling (DPM) using longitudinal data is a challenging machine learning task. Existing DPM algorithms neglect temporal dependencies among measurements, make parametric assumptions about biomarker trajectories, do not model multip...

Machine learning models to predict disease progression among veterans with hepatitis C virus.

PloS one
BACKGROUND: Machine learning (ML) algorithms provide effective ways to build prediction models using longitudinal information given their capacity to incorporate numerous predictor variables without compromising the accuracy of the risk prediction. C...

Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

Clinical lung cancer
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive o...

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks.

NeuroImage. Clinical
We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. Convolutional n...

Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson's Disease.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Parkinson's Disease (PD) is one of the most prevalent neurodegenerative diseases that affects tens of millions of Americans. PD is highly progressive and heterogeneous. Quite a few studies have been conducted in recent years on predictive or disease ...

Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. NAFLD patients have excessive liver fat (steatosis), without other liver diseases and without excessive alcohol consumption. NAFLD consists of a spectr...

Evaluation of serum and salivary interferon-γ levels in patients with oral lichen planus: a systematic review and meta-analysis of case-control studies.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: Cytokines have regulatory and leading roles in the immunopathogenesis of oral lichen planus (OLP). Here, we present the findings of a meta-analysis that evaluated serum and salivary interferon-γ (IFN-γ) levels in patients with OLP compared...