AIMC Topic: Machine Learning

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A machine learning framework with anatomical prior for online dose verification using positron emitters and PET in proton therapy.

Physics in medicine and biology
We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information o...

New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes.

International journal of sports medicine
The purpose of this article is to present how predictive machine learning methods can be utilized for detecting sport injury risk factors in a data-driven manner. The approach can be used for finding new hypotheses for risk factors and confirming the...

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging d...

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...

Convolution neural network for effective burn region segmentation of color images.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn injuries are one of the most severe forms of wounds and trauma across the globe. Automated burn diagnosis methods are needed to provide timely treatment to the concerned patients. Artificial intelligence is playing a vital role in de...

Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives.

Seminars in nuclear medicine
Artificial intelligence and machine learning based approaches are increasingly finding their way into various areas of nuclear medicine imaging. With the technical development of new methods and the expansion to new fields of application, this trend ...

Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken.

Poultry science
Two categories of immune responses-innate and adaptive immunity-have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in...

Skeletal bone age prediction based on a deep residual network with spatial transformer.

Computer methods and programs in biomedicine
OBJECTIVE: Bone age prediction can be performed by medical experts manually assessment of X-ray images of the hand bone. In practice, the workload is huge, resource consumption is large, measurement takes a long time, and it is easily influenced by h...

Myelin detection in fluorescence microscopy images using machine learning.

Journal of neuroscience methods
BACKGROUND: The myelin sheath produced by glial cells insulates the axons, and supports the function of the nervous system. Myelin sheath degeneration causes neurodegenerative disorders, such as multiple sclerosis (MS). There are no therapies for MS ...

SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

Analytical and bioanalytical chemistry
In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Escherichia coli O157:H7 (E. coli O157:H7) to ensure food safety. The SERS nanotags were prepared by co...