AIMC Topic: Algorithms

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Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain.

International journal of neural systems
Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and parallel computing model, combining the spiking and coupled mechanisms of neurons. This paper focuses on how to apply CNP systems to handle the fusion of multi-...

A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds.

Neural networks : the official journal of the International Neural Network Society
A new robust algorithm based on the explanation method SurvLIME called SurvLIME-KS is proposed for explaining machine learning survival models. The algorithm is developed to ensure robustness to cases of a small amount of training data or outliers of...

Classifying the type of delivery from cardiotocographic signals: A machine learning approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cardiotocography (CTG) is the most employed methodology to monitor the foetus in the prenatal phase. Since the evaluation of CTG is often visual, and hence qualitative and too subjective, some automated methods have been int...

Impact of Chemist-In-The-Loop Molecular Representations on Machine Learning Outcomes.

Journal of chemical information and modeling
The development of molecular descriptors is a central challenge in cheminformatics. Most approaches use algorithms that extract atomic environments or end-to-end machine learning. However, a looming question is that how do these approaches compare wi...

Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.

Neural networks : the official journal of the International Neural Network Society
Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Spiking neural networks (SNNs) represent a family of event-driven models...

Multi-AI competing and winning against humans in iterated Rock-Paper-Scissors game.

Scientific reports
Predicting and modeling human behavior and finding trends within human decision-making processes is a major problem of social science. Rock Paper Scissors (RPS) is the fundamental strategic question in many game theory problems and real-world competi...

Learning machine approach reveals microbial signatures of diet and sex in dog.

PloS one
The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already inve...

A brief introduction to concepts and applications of artificial intelligence in dental imaging.

Oral radiology
This report aims to summarize the fundamental concepts of Artificial Intelligence (AI), and to provide a non-exhaustive overview of AI applications in dental imaging, comprising diagnostics, forensics, image processing and image reconstruction. AI ha...

Denoising Algorithm for Event-Related Desynchronization-Based Motor Intention Recognition in Robot-assisted Stroke Rehabilitation Training with Brain-Machine Interaction.

Journal of neuroscience methods
BACKGROUND: Rehabilitation robots integrated with brain-machine interaction (BMI) can facilitate stroke patients' recovery by closing the loop between motor intention and actual movement. The main challenge is to identify the patient's motor intentio...

A data-driven approach to build a predictive model of cancer patients' disease outcome by utilizing co-expression networks.

Computers in biology and medicine
BACKGROUND: Next Generation Sequencing (NGS) technologies have revolutionized genomics data research over the last decades by facilitating high-throughput sequencing of genetic material such as RNA Sequencing (RNAseq). A significant challenge is to e...