AIMC Topic: Machine Learning

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A machine learning framework to determine geolocations from metagenomic profiling.

Biology direct
BACKGROUND: Studies on metagenomic data of environmental microbial samples found that microbial communities seem to be geolocation-specific, and the microbiome abundance profile can be a differentiating feature to identify samples' geolocations. In t...

Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...

Detecting cells in intravital video microscopy using a deep convolutional neural network.

Computers in biology and medicine
The analysis of leukocyte recruitment in intravital video microscopy (IVM) is essential to the understanding of inflammatory processes. However, because IVM images often present a large variety of visual characteristics, it is hard for an expert huma...

Modality independent adversarial network for generalized zero shot image classification.

Neural networks : the official journal of the International Neural Network Society
Zero Shot Learning (ZSL) aims to classify images of unseen target classes by transferring knowledge from source classes through semantic embeddings. The core of ZSL research is to embed both visual representation of object instance and semantic descr...

Age verification using random forests on facial 3D landmarks.

Forensic science international
Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and veri...

The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis.

Computers in biology and medicine
Recently, deep learning frameworks have rapidly become the main methodology for analyzing medical images. Due to their powerful learning ability and advantages in dealing with complex patterns, deep learning algorithms are ideal for image analysis ch...

Emerging use of machine learning and advanced technologies to assess red cell quality.

Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis
Improving blood product quality and patient outcomes is an accepted goal in transfusion medicine research. Thus, there is an urgent need to understand the potential adverse effects on red blood cells (RBCs) during pre-transfusion storage. Current ass...

Spectrophotometric Online Detection of Drinking Water Disinfectant: A Machine Learning Approach.

Sensors (Basel, Switzerland)
The spectra fingerprint of drinking water from a water treatment plant (WTP) is characterised by a number of light-absorbing substances, including organic, nitrate, disinfectant, and particle or turbidity. Detection of disinfectant (monochloramine) c...

Machine Learning Approaches to Analyzing Adverse Events Following Durable LVAD Implantation.

The Annals of thoracic surgery
BACKGROUND: This study employed machine learning approaches to analyze sequences of adverse events (AEs) after left ventricular assist device (LVAD) implantation.

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

Journal of neurointerventional surgery
BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographi...