AIMC Topic: Algorithms

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ADHD classification by dual subspace learning using resting-state functional connectivity.

Artificial intelligence in medicine
As one of the most common neurobehavioral diseases in school-age children, Attention Deficit Hyperactivity Disorder (ADHD) has been increasingly studied in recent years. But it is still a challenge problem to accurately identify ADHD patients from he...

Determining of the optimized dimensions of the Marinelli beaker containing source with inhomogeneous emission rate by using genetic algorithm coupled with MCNP and determining distribution type by neural networks.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
In order to determine the activity of C137s in soil resulting from nuclear accidents or fallouts, the best choice is to use HPGe detectors due to their best energy resolutions. In this regard, in order to enhance the detection efficiency, the Marinel...

A Deep Learning Framework for Assessing Physical Rehabilitation Exercises.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Computer-aided assessment of physical rehabilitation entails evaluation of patient performance in completing prescribed rehabilitation exercises, based on processing movement data captured with a sensory system. Despite the essential role of rehabili...

Machine learning derived input-function in a dynamic F-FDG PET study of mice.

Biomedical physics & engineering express
Tracer kinetic modelling, based on dynamic F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. O...

Validation of a Deep Learning System for the Full Automation of Bite and Meal Duration Analysis of Experimental Meal Videos.

Nutrients
Eating behavior can have an important effect on, and be correlated with, obesity and eating disorders. Eating behavior is usually estimated through self-reporting measures, despite their limitations in reliability, based on ease of collection and ana...

Automatic Hierarchical Classification of Kelps Using Deep Residual Features.

Sensors (Basel, Switzerland)
Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes f...

Transfer Learning in ECG Classification from Human to Horse Using a Novel Parallel Neural Network Architecture.

Scientific reports
Automatic or semi-automatic analysis of the equine electrocardiogram (eECG) is currently not possible because human or small animal ECG analysis software is unreliable due to a different ECG morphology in horses resulting from a different cardiac inn...

VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning.

PLoS computational biology
Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches, and there remains incomplete understanding of AMR mechanisms for many pathogen-antimicrobial combin...

Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Segmentation is a crucial step in multiple biomechanics and orthopedics applications. The time-intensiveness and expertise requirements of medical image segmentation present a significant bottleneck for corresponding workflo...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Journal of visualized experiments : JoVE
Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common MCI tests are time-consuming such that indiscriminate massive screening would not be cost-effect...