AIMC Topic: Machine Learning

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Farmland quality assessment using deep fully convolutional neural networks.

Environmental monitoring and assessment
Farmland is the cornerstone of agriculture and is important for food security and social production. Farmland assessment is essential but traditional methods are usually expensive and slow. Deep learning methods have been developed and widely applied...

Application of Machine Learning in Intelligent Medical Image Diagnosis and Construction of Intelligent Service Process.

Computational intelligence and neuroscience
The introduction of digital technology in the healthcare industry is marked by ongoing difficulties with implementation and use. Slow progress has been made in unifying different healthcare systems, and much of the globe still lacks a fully integrate...

Statistical approaches to identifying significant differences in predictive performance between machine learning and classical statistical models for survival data.

PloS one
Research that seeks to compare two predictive models requires a thorough statistical approach to draw valid inferences about comparisons between the performance of the two models. Researchers present estimates of model performance with little evidenc...

In-silico generation of high-dimensional immune response data in patients using a deep neural network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Technologies for single-cell profiling of the immune system have enabled researchers to extract rich interconnected networks of cellular abundance, phenotypical and functional cellular parameters. These studies can power machine learning approaches t...

Prediction of coronary heart disease in gout patients using machine learning models.

Mathematical biosciences and engineering : MBE
Growing evidence shows that there is an increased risk of cardiovascular diseases among gout patients, especially coronary heart disease (CHD). Screening for CHD in gout patients based on simple clinical factors is still challenging. Here we aim to b...

Multiple machine learning methods aided virtual screening of Na 1.5 inhibitors.

Journal of cellular and molecular medicine
Na 1.5 sodium channels contribute to the generation of the rapid upstroke of the myocardial action potential and thereby play a central role in the excitability of myocardial cells. At present, the patch clamp method is the gold standard for ion chan...

Diagnosis of Operating Conditions of the Electrical Submersible Pump via Machine Learning.

Sensors (Basel, Switzerland)
In wells that operate by electrical submersible pump (ESP), the use of automation tools becomes essential in the interpretation of data. However, the fact that the wells work with automated systems does not guarantee the early diagnosis of operating ...

Machine Learning Estimation of the Phase at the Fading Points of an OFDR-Based Distributed Sensor.

Sensors (Basel, Switzerland)
The paper reports a machine learning approach for estimating the phase in a distributed acoustic sensor implemented using optical frequency domain reflectometry, with enhanced robustness at the fading points. A neural network configuration was traine...

On the ability of machine learning methods to discover novel scaffolds.

Journal of molecular modeling
The recent advances in the application of machine learning to drug discovery have made it a 'hot topic' for research, with hundreds of academic groups and companies integrating machine learning into their drug discovery projects. Nevertheless, there ...