AIMC Topic: Algorithms

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Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Face recognition success rate is influenced by illumination, expression, posture change, and other factors, which is due to the low generalization ability of a single convolutional neural network. A new face recognition meth...

Machine Learning Clustering for Blood Pressure Variability Applied to Systolic Blood Pressure Intervention Trial (SPRINT) and the Hong Kong Community Cohort.

Hypertension (Dallas, Tex. : 1979)
Visit-to-visit blood pressure variability (BPV) has been shown to be a predictor of cardiovascular disease. We aimed to classify the BPV levels using different machine learning algorithms. Visit-to-visit blood pressure readings were extracted from th...

RNN-Aided Human Velocity Estimation from a Single IMU.

Sensors (Basel, Switzerland)
Pedestrian Dead Reckoning (PDR) uses inertial measurement units (IMUs) and combines velocity and orientation estimates to determine a position. The estimation of the velocity is still challenging, as the integration of noisy acceleration and angular ...

Comparing Person-Specific and Independent Models on Subject-Dependent and Independent Human Activity Recognition Performance.

Sensors (Basel, Switzerland)
The distinction between subject-dependent and subject-independent performance is ubiquitous in the human activity recognition (HAR) literature. We assess whether HAR models really do achieve better subject-dependent performance than subject-independe...

Finding undiagnosed patients with hepatitis C infection: an application of artificial intelligence to patient claims data.

Scientific reports
Hepatitis C virus (HCV) remains a significant public health challenge with approximately half of the infected population untreated and undiagnosed. In this retrospective study, predictive models were developed to identify undiagnosed HCV patients usi...

Don't dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning.

BMC medical research methodology
BACKGROUND: Machine learning approaches have become increasingly popular modeling techniques, relying on data-driven heuristics to arrive at its solutions. Recent comparisons between these algorithms and traditional statistical modeling techniques ha...

Analysis of high-dimensional genomic data using MapReduce based probabilistic neural network.

Computer methods and programs in biomedicine
BACKGROUND: The size of genomics data has been growing rapidly over the last decade. However, the conventional data analysis techniques are incapable of processing this huge amount of data. For the efficient processing of high dimensional datasets, i...

Brain-Computer Interface-Based Humanoid Control: A Review.

Sensors (Basel, Switzerland)
A Brain-Computer Interface (BCI) acts as a communication mechanism using brain signals to control external devices. The generation of such signals is sometimes independent of the nervous system, such as in Passive BCI. This is majorly beneficial for ...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

BioMed research international
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...