AIMC Topic: Machine Learning

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Emerging role of eHealth in the identification of very early inflammatory rheumatic diseases.

Best practice & research. Clinical rheumatology
Digital health or eHealth technologies, notably pervasive computing, robotics, big-data, wearable devices, machine learning, and artificial intelligence (AI), have opened unprecedented opportunities as to how the diseases are diagnosed and managed wi...

Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder.

BioMed research international
Computational drug repositioning, designed to identify new indications for existing drugs, significantly reduced the cost and time involved in drug development. Prediction of drug-disease associations is promising for drug repositioning. Recent years...

Artificial intelligence as an emerging technology in the current care of neurological disorders.

Journal of neurology
BACKGROUND: Artificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., m...

Machine learning for mixture toxicity analysis based on high-throughput printing technology.

Talanta
Analysis on mixture toxicity (Mix-tox) of the multi-chemical space is constantly followed with interest for many researchers. Conventional toxicity tests with time-consuming and costly operations make researchers can only establish some toxicity pred...

Locally connected spiking neural networks for unsupervised feature learning.

Neural networks : the official journal of the International Neural Network Society
In recent years, spiking neural networks (SNNs) have demonstrated great success in completing various machine learning tasks. We introduce a method for learning image features with locally connected layers in SNNs using a spike-timing-dependent plast...

Looking beyond the hype: Applied AI and machine learning in translational medicine.

EBioMedicine
Big data problems are becoming more prevalent for laboratory scientists who look to make clinical impact. A large part of this is due to increased computing power, in parallel with new technologies for high quality data generation. Both new and old t...

FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule.

International journal of molecular sciences
DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these met...

Homology analysis of malware based on ensemble learning and multifeatures.

PloS one
With the exponential increase in malware, homology analysis has become a hot research topic in the malware detection field. This paper proposes MHAS, a malware homology analysis system based on ensemble learning and multifeatures. MHAS generates gray...

Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game.

Neural networks : the official journal of the International Neural Network Society
Deep Reinforcement Learning (RL) demonstrates excellent performance on tasks that can be solved by trained policy. It plays a dominant role among cutting-edge machine learning approaches using multi-layer Neural networks (NNs). At the same time, Deep...

Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling.

Sensors (Basel, Switzerland)
In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pu...