AIMC Topic: Machine Learning

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A review of recent developments in the application of machine learning in solar thermal collector modelling.

Environmental science and pollution research international
Over the past few decades, the popularity of solar thermal collectors has increased dramatically because of many significant advantages like being a free, natural, environmentally friendly and permanent energy source. Today, developing and optimising...

Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment.

Current psychiatry reports
PURPOSE OF REVIEW: This review will cover the most relevant findings on the use of machine learning (ML) techniques in the field of non-affective psychosis, by summarizing the studies published in the last three years focusing on illness detection an...

A Novel Multiple-View Adversarial Learning Network for Unsupervised Domain Adaptation Action Recognition.

IEEE transactions on cybernetics
Abstract-domain adaptation action recognition is a hot research topic in machine learning and some effective approaches have been proposed. However, samples in the target domain with label information are often required by these approaches. Moreover,...

Effective Transfer Learning Algorithm in Spiking Neural Networks.

IEEE transactions on cybernetics
As the third generation of neural networks, spiking neural networks (SNNs) have gained much attention recently because of their high energy efficiency on neuromorphic hardware. However, training deep SNNs requires many labeled data that are expensive...

UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues.

Communications biology
Upcoming technologies enable routine collection of highly multiplexed (20-60 channel), subcellular resolution images of mammalian tissues for research and diagnosis. Extracting single cell data from such images requires accurate image segmentation, a...

Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation.

Scientific reports
Leading a sedentary lifestyle may cause numerous health problems. Therefore, passive lifestyle changes should be given priority to avoid severe long-term damage. Automatic health coaching system may help people manage a healthy lifestyle with continu...

A Pilot Machine Learning Study Using Trauma Admission Data to Identify Risk for High Length of Stay.

Surgical innovation
INTRODUCTION: Trauma patients have diverse resource needs due to variable mechanisms and injury patterns. The aim of this study was to build a tool that uses only data available at time of admission to predict prolonged hospital length of stay (LOS).

Universal machine-learning algorithm for predicting adsorption performance of organic molecules based on limited data set: Importance of feature description.

The Science of the total environment
Adsorption of organic molecules from aqueous solution offers a simple and effective method for their removal. Recently, there have been several attempts to apply machine learning (ML) for this problem. To this end, polyparameter linear free energy re...

Prediction of evaporation from dam reservoirs under climate change using soft computing techniques.

Environmental science and pollution research international
This study aimed to predict evaporation from dam reservoirs using artificial intelligence considering climate change. Mahabad Dam, near Lake Urmia, in northwestern Iran, is used to investigate the proposed approach. There are three parts to the study...

The synergy of synchrotron imaging and convolutional neural networks towards the detection of human micro-scale bone architecture and damage.

Journal of the mechanical behavior of biomedical materials
The growing health and economic burden of bone fractures, their intricate multiscale features and the existing knowledge gaps in the comprehension of micro-scale bone damage occurrence make fracture diagnosis a challenging issue. In this scenario, de...