AIMC Topic: Area Under Curve

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Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Human brain mapping
Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in i...

Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data, with each view correspondi...

Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.

Journal of psychiatric research
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current stud...

Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article fe...

How can machine-learning methods assist in virtual screening for hyperuricemia? A healthcare machine-learning approach.

Journal of biomedical informatics
OBJECT: Our purpose was to develop a new machine-learning approach (a virtual health check-up) toward identification of those at high risk of hyperuricemia. Applying the system to general health check-ups is expected to reduce medical costs compared ...

Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...

Classifying publications from the clinical and translational science award program along the translational research spectrum: a machine learning approach.

Journal of translational medicine
BACKGROUND: Translational research is a key area of focus of the National Institutes of Health (NIH), as demonstrated by the substantial investment in the Clinical and Translational Science Award (CTSA) program. The goal of the CTSA program is to acc...

Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Diabetic retinopathy (DR) is a progressive disease, and its detection at an early stage is crucial for saving a patient's vision. An automated screening system for DR can help in reduce the chances of complete blindness due to DR along with lowering ...

Enhancing deep convolutional neural network scheme for breast cancer diagnosis with unlabeled data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this study we developed a graph based semi-supervised learning (SSL) scheme using deep convolutional neural network (CNN) for breast cancer diagnosis. CNN usually needs a large amount of labeled data for training and fine tuning the parameters, an...