AIMC Topic: Machine Learning

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And the nominees are: Using design-awards datasets to build computational aesthetic evaluation model.

PloS one
Aesthetic perception is a human instinct that is responsive to multimedia stimuli. Giving computers the ability to assess human sensory and perceptual experience of aesthetics is a well-recognized need for the intelligent design industry and multimed...

Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...

A survey on machine and statistical learning for longitudinal analysis of neuroimaging data in Alzheimer's disease.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Recently, longitudinal studies of Alzheimer's disease have gathered a substantial amount of neuroimaging data. New methods are needed to successfully leverage and distill meaningful information on the progression of the dis...

An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.

IEEE transactions on biomedical circuits and systems
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...

Multi-media biomarkers: Integrating information to improve lead exposure assessment.

Environmental research
Exposure assessment traditionally relies on biomarkers that measure chemical concentrations in individual biological media (i.e., blood, urine, etc.). However, chemicals distribute unevenly among different biological media; thus, each medium provides...

Diagnosis and classification of cancer using hybrid model based on ReliefF and convolutional neural network.

Medical hypotheses
Machine learning and deep learning methods aims to discover patterns out of datasets such as, microarray data and medical data. In recent years, the importance of producing microarray data from tissue and cell samples and analyzing these microarray d...

Multi-context aware user-item embedding for recommendation.

Neural networks : the official journal of the International Neural Network Society
Real recommender systems usually contain various auxiliary information. Some of the most recent works make meaningful exploration of incorporating auxiliary information into the representation model for competitive recommendation. However, learning u...

Machine learning approaches for analyzing and enhancing molecular dynamics simulations.

Current opinion in structural biology
Molecular dynamics (MD) has become a powerful tool for studying biophysical systems, due to increasing computational power and availability of software. Although MD has made many contributions to better understanding these complex biophysical systems...

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types. The main reasons are potential improvements in energy efficiency and memory foot...

MMPdb and MitoPredictor: Tools for facilitating comparative analysis of animal mitochondrial proteomes.

Mitochondrion
Data on experimentally-characterized animal mitochondrial proteomes (mt-proteomes) are limited to a few model organisms and are scattered across multiple databases, impeding a comparative analysis. We developed two resources to address these problems...