AIMC Topic: Machine Learning

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Classification of ransomware using different types of neural networks.

Scientific reports
Malware threat the security of computers and Internet. Among the diversity of malware, we have "ransomware". Its main objective is to prevent and block access to user data and computers in exchange for a ransom, once paid, the data will be liberated....

Predicting Breast Cancer Based on Optimized Deep Learning Approach.

Computational intelligence and neuroscience
Breast cancer is a dangerous disease with a high morbidity and mortality rate. One of the most important aspects in breast cancer treatment is getting an accurate diagnosis. Machine-learning (ML) and deep learning techniques can help doctors in makin...

Artificial intelligence applied to fetal MRI: A scoping review of current research.

The British journal of radiology
Artificial intelligence (AI) is defined as the development of computer systems to perform tasks normally requiring human intelligence. A subset of AI, known as machine learning (ML), takes this further by drawing inferences from patterns in data to '...

Machine learning algorithm for precise prediction of 2'-O-methylation (Nm) sites from experimental RiboMethSeq datasets.

Methods (San Diego, Calif.)
Analysis of epitranscriptomic RNA modifications by deep sequencing-based approaches brings an essential contribution to the general knowledge on their precise locations and relative stoichiometry in cellular RNAs. To reveal RNA modifications, several...

PharmRF: A machine-learning scoring function to identify the best protein-ligand complexes for structure-based pharmacophore screening with high enrichments.

Journal of computational chemistry
Structure-based pharmacophore models are often developed by selecting a single protein-ligand complex with good resolution and better binding affinity data which prevents the analysis of other structures having a similar potential to act as better te...

How Validation Methodology Influences Human Activity Recognition Mobile Systems.

Sensors (Basel, Switzerland)
In this article, we introduce explainable methods to understand how Human Activity Recognition (HAR) mobile systems perform based on the chosen validation strategies. Our results introduce a new way to discover potential bias problems that overestima...

Sources of Risk of AI Systems.

International journal of environmental research and public health
Artificial intelligence can be used to realise new types of protective devices and assistance systems, so their importance for occupational safety and health is continuously increasing. However, established risk mitigation measures in software develo...

Improving multiple model ensemble predictions of daily precipitation and temperature through machine learning techniques.

Scientific reports
Multi-Model Ensembles (MMEs) are used for improving the performance of GCM simulations. This study evaluates the performance of MMEs of precipitation, maximum temperature and minimum temperature over a tropical river basin in India developed by vario...

Assessing radiomics feature stability with simulated CT acquisitions.

Scientific reports
Medical imaging quantitative features had once disputable usefulness in clinical studies. Nowadays, advancements in analysis techniques, for instance through machine learning, have enabled quantitative features to be progressively useful in diagnosis...