AIMC Topic: Longitudinal Studies
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A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.
NeuroImage
Nov 1, 2019
Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algo...
Machine Learning to Predict Acute Kidney Injury.
American journal of kidney diseases : the official journal of the National Kidney Foundation
Oct 31, 2019
Environmental odour management by artificial neural network - A review.
Environment international
Oct 29, 2019
Unwanted odour emissions are considered air pollutants that may cause detrimental impacts to the environment as well as an indicator of unhealthy air to the affected individuals resulting in annoyance and health related issues. These pollutants are c...
Analysis of substance use and its outcomes by machine learning I. Childhood evaluation of liability to substance use disorder.
Drug and alcohol dependence
Oct 22, 2019
BACKGROUND: Substance use disorder (SUD) exacts enormous societal costs in the United States, and it is important to detect high-risk youths for prevention. Machine learning (ML) is the method to find patterns and make prediction from data. We hypoth...
Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation.
Radiology
Oct 22, 2019
Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive pulmonary disease (COPD). Conventional noncontrast CT provides airway and parenchymal measurements but cannot be used to directly determine lung funct...
Recurrent Neural Networks for Early Detection of Heart Failure From Longitudinal Electronic Health Record Data: Implications for Temporal Modeling With Respect to Time Before Diagnosis, Data Density, Data Quantity, and Data Type.
Circulation. Cardiovascular quality and outcomes
Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Smoking
Alcohol Drinking
California
Vital Signs
Machine Learning
Male
Electronic Health Records
Diagnosis, Computer-Assisted
Primary Health Care
Female
Incidence
Longitudinal Studies
Reproducibility of Results
Time Factors
Predictive Value of Tests
Risk Factors
Humans
Heart Failure
Neural Networks, Computer
Early Diagnosis
Analysis of substance use and its outcomes by machine learning: II. Derivation and prediction of the trajectory of substance use severity.
Drug and alcohol dependence
Oct 1, 2019
BACKGROUND: This longitudinal study explored the utility of machine learning (ML) methodology in predicting the trajectory of severity of substance use from childhood to thirty years of age using a set of psychological and health characteristics.
Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.
International journal of medical informatics
Sep 23, 2019
INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An effective depression risk prediction model can provide insights on the disease progression and potentially inform timely targeted interventions. Theref...
Machine learning discovery of longitudinal patterns of depression and suicidal ideation.
PloS one
Sep 20, 2019
BACKGROUND AND AIM: Depression is often accompanied by thoughts of self-harm, which are a strong predictor of subsequent suicide attempt and suicide death. Few empirical data are available regarding the temporal correlation between depression symptom...
An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population.
Chest
Sep 19, 2019
BACKGROUND: Prediction of future lung function will enable the identification of individuals at high risk of developing COPD, but the trajectory of lung function decline varies greatly among individuals. This study involved the development and valida...
Sex Factors
Body Height
Alcohol Drinking
Spirometry
Triglycerides
Serum Albumin
Leukocyte Count
Vital Capacity
Humans
Bronchodilator Agents
Forced Expiratory Volume
Machine Learning
Cigarette Smoking
Algorithms
Alkaline Phosphatase
Hematocrit
Aging
Female
Dyspnea
Middle Aged
Electrocardiography
Adult
Risk Assessment
Serum Globulins
Longitudinal Studies
Pulmonary Disease, Chronic Obstructive
Lung
Age Factors
Male
Cohort Studies
Cough
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