AIMC Topic: Probability

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Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.

Risk analysis : an official publication of the Society for Risk Analysis
Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and vi...

Machine learning in critical care: state-of-the-art and a sepsis case study.

Biomedical engineering online
BACKGROUND: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This challenge entails the dauntin...

Deep CNNs with Robust LBP Guiding Pooling for Face Recognition.

Sensors (Basel, Switzerland)
Pooling layer in Convolutional Neural Networks (CNNs) is designed to reduce dimensions and computational complexity. Unfortunately, CNN is easily disturbed by noise in images when extracting features from input images. The traditional pooling layer d...

A 0.086-mm 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS.

IEEE transactions on biomedical circuits and systems
Shifting computing architectures from von Neumann to event-based spiking neural networks (SNNs) uncovers new opportunities for low-power processing of sensory data in applications such as vision or sensorimotor control. Exploring roads toward cogniti...

Accelerating deep learning with memcomputing.

Neural networks : the official journal of the International Neural Network Society
Restricted Boltzmann machines (RBMs) and their extensions, often called "deep-belief networks", are powerful neural networks that have found applications in the fields of machine learning and artificial intelligence. The standard way to train these m...

Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.

Genetic epidemiology
The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions is an important but challenging undertaking for genetic studies. Many complex phenotypes such as dise...

Utilizing soft constraints to enhance medical relation extraction from the history of present illness in electronic medical records.

Journal of biomedical informatics
Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous researches utilizing machine learning algorithms judge the semantic types of medical concept pair menti...

Detecting drug-resistant tuberculosis in chest radiographs.

International journal of computer assisted radiology and surgery
PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decreasing over the last years, the rise of drug-resistant tuberculosis has reduced the chance of contro...

Variable importance for sustaining macrophyte presence via random forests: data imputation and model settings.

Scientific reports
Data sets plagued with missing data and performance-affecting model parameters represent recurrent issues within the field of data mining. Via random forests, the influence of data reduction, outlier and correlated variable removal and missing data i...

PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.

Journal of biomedical informatics
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...