AIMC Topic: Disease Progression

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Fitting prediction rule ensembles to psychological research data: An introduction and tutorial.

Psychological methods Feb 10, 2020
Prediction rule ensembles (PREs) are a relatively new statistical learning method, which aim to strike a balance between predictive performance and interpretability. Starting from a decision tree ensemble, like a boosted tree ensemble or a random for...
Young Adult Adult Biomedical Research Male Middle Aged Humans Machine Learning Prognosis Female Statistics as Topic Depressive Disorder Disease Progression Anxiety Disorders Adolescent Psychology
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Deep learning risk assessment models for predicting progression of radiographic medial joint space loss over a 48-MONTH follow-up period.

Osteoarthritis and cartilage Feb 6, 2020
OBJECTIVE: To develop and evaluate deep learning (DL) risk assessment models for predicting the progression of radiographic medial joint space loss using baseline knee X-rays.
Aged Deep Learning Male Area Under Curve Middle Aged Radiography Risk Assessment Osteoarthritis, Knee Humans Disease Progression Female Risk Factors
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Predicting 10-Year Risk of End-Organ Complications of Type 2 Diabetes With and Without Metabolic Surgery: A Machine Learning Approach.

Diabetes care Feb 6, 2020
OBJECTIVE: To construct and internally validate prediction models to estimate the risk of long-term end-organ complications and mortality in patients with type 2 diabetes and obesity that can be used to inform treatment decisions for patients and pra...
Female Aged Aged, 80 and over Young Adult Adult Machine Learning Computer Simulation Prognosis Retrospective Studies Diabetes Mellitus, Type 2 Follow-Up Studies Bariatric Surgery Organs at Risk Diabetes Complications Male Middle Aged Disease Progression Adolescent Time Factors Humans
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Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

NeuroImage. Clinical Jan 26, 2020
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether ...
Aged Male Middle Aged Disease Progression Cognitive Dysfunction Machine Learning Brain Prognosis Female Humans Magnetic Resonance Imaging Models, Neurological Alzheimer Disease Image Interpretation, Computer-Assisted Neuroimaging
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Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.

Scientific reports Jan 24, 2020
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...
Deep Learning Chronic Disease Bayes Theorem Patient Readmission Forecasting Odds Ratio Communicable Diseases Medical Records Systems, Computerized Intensive Care Units Risk Humans Sensitivity and Specificity Neural Networks, Computer Disease Progression Algorithms
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A Novel Deep Learning Approach with a 3D Convolutional Ladder Network for Differential Diagnosis of Idiopathic Normal Pressure Hydrocephalus and Alzheimer's Disease.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jan 22, 2020
PURPOSE: Idiopathic normal pressure hydrocephalus (iNPH) and Alzheimer's disease (AD) are geriatric diseases and common causes of dementia. Recently, many studies on the segmentation, disease detection, or classification of MRI using deep learning ha...
Humans Artificial Intelligence Brain Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging Diagnosis, Differential Male Female Alzheimer Disease Middle Aged Reproducibility of Results Pattern Recognition, Automated Disease Progression Aged Neuroimaging Case-Control Studies Aged, 80 and over Hydrocephalus, Normal Pressure Diagnosis, Computer-Assisted
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Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Artificial intelligence in medicine Jan 21, 2020
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...
Disease Progression Aged Affect Anxiety Memory Humans Cognition Aged, 80 and over Sleep Wake Disorders Machine Learning Parkinson Disease Adult Autonomic Nervous System Prognosis Male Female Middle Aged
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A survey on machine and statistical learning for longitudinal analysis of neuroimaging data in Alzheimer's disease.

Computer methods and programs in biomedicine Jan 20, 2020
BACKGROUND AND OBJECTIVES: Recently, longitudinal studies of Alzheimer's disease have gathered a substantial amount of neuroimaging data. New methods are needed to successfully leverage and distill meaningful information on the progression of the dis...
Neuroimaging Humans Machine Learning Disease Progression Longitudinal Studies Alzheimer Disease
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DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet.

Medical physics Jan 20, 2020
PURPOSE: Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM on the follow-up magn...
Disease Progression Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Glioblastoma Humans Area Under Curve
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Prediction of progression from pre-diabetes to diabetes: Development and validation of a machine learning model.

Diabetes/metabolism research and reviews Jan 14, 2020
AIMS: Identification, a priori, of those at high risk of progression from pre-diabetes to diabetes may enable targeted delivery of interventional programmes while avoiding the burden of prevention and treatment in those at low risk. We studied whethe...
Israel United Kingdom Prediabetic State Male Middle Aged Risk Assessment Disease Progression Cohort Studies Female Time Factors Risk Factors Canada Aged Diabetes Mellitus Aged, 80 and over Humans Follow-Up Studies Adult Patient Selection Machine Learning Databases, Factual Prognosis Electronic Health Records
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