AIMC Topic: Algorithms

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How Confounder Strength Can Affect Allocation of Resources in Electronic Health Records.

Perspectives in health information management
When electronic health record (EHR) data are used, multiple approaches may be available for measuring the same variable, introducing potentially confounding factors. While additional information may be gleaned and residual confounding reduced through...

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Frontiers in bioscience (Landmark edition)
Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing A...

Multiscale High-Level Feature Fusion for Histopathological Image Classification.

Computational and mathematical methods in medicine
Histopathological image classification is one of the most important steps for disease diagnosis. We proposed a method for multiclass histopathological image classification based on deep convolutional neural network referred to as coding network. It c...

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

Computational and mathematical methods in medicine
Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The inv...

Prediction models to identify individuals at risk of metabolic syndrome who are unlikely to participate in a health intervention program.

International journal of medical informatics
OBJECTIVES: Since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in strategies to improve implementation of the program based on predictive analytics has grown. We investigated the performance of...

Non-water-suppressed H FID-MRSI at 3T and 9.4T.

Magnetic resonance in medicine
PURPOSE: This study investigates metabolite concentrations using metabolite-cycled H free induction decay (FID) magnetic resonance spectroscopic imaging (MRSI) at ultra-high fields.

Lung Lesion Detection in CT Scan Images Using the Fuzzy Local Information Cluster Means (FLICM) Automatic Segmentation Algorithm and Back Propagation Network Classification.

Asian Pacific journal of cancer prevention : APJCP
Lung cancer is a frequently lethal disease often causing death of human beings at an early age because of uncontrolled cell growth in the lung tissues. The diagnostic methods available are less than effective for detection of cancer. Therefore an aut...

Reactive navigation in extremely dense and highly intricate environments.

PloS one
Reactive navigation is a well-known paradigm for controlling an autonomous mobile robot, which suggests making all control decisions through some light processing of the current/recent sensor data. Among the many advantages of this paradigm are: 1) t...

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification.

International journal of neural systems
The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the ...