AIMC Topic: Early Diagnosis

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Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Knee osteoarthritis (OA) is one major cause of activity limitation and physical disability in older adults. Early detection and intervention can help slow down the OA degeneration. Physicians' grading based on visual inspection is subjective, varied ...

Identifying Children With Clinical Language Disorder: An Application of Machine-Learning Classification.

Journal of learning disabilities
In this study, we identified child- and family-level characteristics most strongly associated with clinical identification of language disorder for preschool-aged children. We used machine learning to identify variables that best classified children ...

Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques.

PloS one
OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the ...

Use of machine learning techniques in the development and refinement of a predictive model for early diagnosis of ankylosing spondylitis.

Clinical rheumatology
OBJECTIVE: To develop a predictive mathematical model for the early identification of ankylosing spondylitis (AS) based on the medical and pharmacy claims history of patients with and without AS.

A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data.

International journal of environmental research and public health
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine osteoarthritis. A correct prediction of osteoarthritis is an essential step to effectively diagnose and prevent severe osteoarthritis. Osteoarthritis i...

Developing neural network models for early detection of cardiac arrest in emergency department.

The American journal of emergency medicine
BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardi...

Early Alzheimer's disease diagnosis based on EEG spectral images using deep learning.

Neural networks : the official journal of the International Neural Network Society
Early diagnosis of Alzheimer's disease (AD) is a proceeding hot issue along with a sharp upward trend in the incidence rate. Recently, early diagnosis of AD employing Electroencephalogram (EEG) as a specific hallmark has been an increasingly signific...

A Parametric Design Method for Optimal Quick Diagnostic Software.

Sensors (Basel, Switzerland)
Fault diagnostic software is required to respond to faults as early as possible in time-critical applications. However, the existing methods based on early diagnosis are not adequate. First, there is no common standard to quantify the response time o...

A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a fully developed computer aided diagnosis (CAD) system for early knee OsteoArthritis (OA) detection using knee X-ray imaging and machine learning algorithms. The X-ray images are first preprocessed in the Fourier domain using a c...