AIMC Topic: Machine Learning

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Comparing context-dependent call sequences employing machine learning methods: an indication of syntactic structure of greater horseshoe bats.

The Journal of experimental biology
For analysis of vocal syntax, accurate classification of call sequence structures in different behavioural contexts is essential. However, an effective, intelligent program for classifying call sequences from numerous recorded sound files is still la...

Predicting fish kills and toxic blooms in an intensive mariculture site in the Philippines using a machine learning model.

The Science of the total environment
Harmful algal blooms (HABs) that produce toxins and those that lead to fish kills are global problems that appear to be increasing in frequency and expanding in area. One way to help mitigate their impacts on people's health and livelihoods is to dev...

CS-MRI reconstruction based on analysis dictionary learning and manifold structure regularization.

Neural networks : the official journal of the International Neural Network Society
Compressed sensing (CS) significantly accelerates magnetic resonance imaging (MRI) by allowing the exact reconstruction of image from highly undersampling k-space data. In this process, the high sparsity obtained by the learned dictionary and exploit...

Machine learning algorithms, bull genetic information, and imbalanced datasets used in abortion incidence prediction models for Iranian Holstein dairy cattle.

Preventive veterinary medicine
The ability to predict abortion incidence, especially in regions with high abortion rates (e.g., Iran), helps improve reproductive performance and, thereby, dairy farm profitability. The objective of this study was to predict pregnancy loss in Irania...

Modeling aspects of the language of life through transfer-learning protein sequences.

BMC bioinformatics
BACKGROUND: Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary information. However, for some applica...

Representation learning for clinical time series prediction tasks in electronic health records.

BMC medical informatics and decision making
BACKGROUND: Electronic health records (EHRs) provide possibilities to improve patient care and facilitate clinical research. However, there are many challenges faced by the applications of EHRs, such as temporality, high dimensionality, sparseness, n...

Prediction of Skin Disease with Three Different Feature Selection Techniques Using Stacking Ensemble Method.

Applied biochemistry and biotechnology
Skin disease is the most common problem between people. Due to pollution and deployment of ozone layer, harmful UV rays of sun burn the skin and develop various types of skin diseases. Nowadays, machine learning and deep learning algorithms are gener...

Artificial intelligence in medical imaging.

Magnetic resonance imaging
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...