AIMC Topic: Machine Learning

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A machine learning approach to detect changes in gait parameters following a fatiguing occupational task.

Ergonomics
The purpose of this study is to provide a method for classifying non-fatigued vs. fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction ($1 Recognizer) along with the support vect...

Using Big Data Analytics to Advance Precision Radiation Oncology.

International journal of radiation oncology, biology, physics
Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinicall...

A machine learning approach for automated assessment of retinal vasculature in the oxygen induced retinopathy model.

Scientific reports
Preclinical studies of vascular retinal diseases rely on the assessment of developmental dystrophies in the oxygen induced retinopathy rodent model. The quantification of vessel tufts and avascular regions is typically computed manually from flat mou...

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

Cell chemical biology
In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, who...

Deep learning with convolutional neural network in radiology.

Japanese journal of radiology
Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the...

Using Machine Learning to Improve the Prediction of Functional Outcome in Ischemic Stroke Patients.

IEEE/ACM transactions on computational biology and bioinformatics
Ischemic stroke is a leading cause of disability and death worldwide among adults. The individual prognosis after stroke is extremely dependent on treatment decisions physicians take during the acute phase. In the last five years, several scores such...

Using machine-learning to optimize phase contrast in a low-cost cellphone microscope.

PloS one
Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost....

Accounting for Label Uncertainty in Machine Learning for Detection of Acute Respiratory Distress Syndrome.

IEEE journal of biomedical and health informatics
When training a machine learning algorithm for a supervised-learning task in some clinical applications, uncertainty in the correct labels of some patients may adversely affect the performance of the algorithm. For example, even clinical experts may ...

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

The Journal of arthroplasty
This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in ...

Possible world based consistency learning model for clustering and classifying uncertain data.

Neural networks : the official journal of the International Neural Network Society
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possib...