AIMC Topic: Algorithms

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A3SOM, abstained explainable semi-supervised neural network based on self-organizing map.

PloS one
In the sea of data generated daily, unlabeled samples greatly outnumber labeled ones. This is due to the fact that, in many application areas, labels are scarce or hard to obtain. In addition, unlabeled samples might belong to new classes that are no...

Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment. Although radiography is the most used technique in clinical practice, it is difficult to accurately rule out rotator cuff tears as an initial imaging...

Target-oriented deep learning-based image registration with individualized test-time adaptation.

Medical physics
BACKGROUND: A classic approach in medical image registration is to formulate an optimization problem based on the image pair of interest, and seek a deformation vector field (DVF) to minimize the corresponding objective, often iteratively. It has a c...

Deep Learning-Based Image Analysis of Liver Steatosis in Mouse Models.

The American journal of pathology
The incidence of nonalcoholic fatty liver disease is a continuously growing health problem worldwide, along with obesity. Therefore, novel methods to both efficiently study the manifestation of nonalcoholic fatty liver disease and to analyze drug eff...

NSICA: Multi-objective imperialist competitive algorithm for feature selection in arrhythmia diagnosis.

Computers in biology and medicine
This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) to solve optimal feature selection problems. The NSICA is a multi-objective and discrete version of the original Imperialist Competitive Algorithm (ICA) t...

Stimulation-mediated reverse engineering of silent neural networks.

Journal of neurophysiology
Reconstructing connectivity of neuronal networks from single-cell activity is essential to understanding brain function, but the challenge of deciphering connections from populations of silent neurons has been largely unmet. We demonstrate a protocol...

Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
This study aimed to develop an algorithm to automatically segment the oral potentially malignant diseases (OPMDs) and oral cancers (OCs) of all oral subsites with various deep convolutional neural network applications. A total of 510 intraoral images...

Omnidirectional Continuous Movement Method of Dual-Arm Robot in a Space Station.

Sensors (Basel, Switzerland)
The burgeoning complexity of space missions has amplified the research focus on robots that are capable of assisting astronauts in accomplishing tasks within space stations. Nevertheless, these robots grapple with substantial mobility challenges in a...

A comparison of point-tracking algorithms in ultrasound videos from the upper limb.

Biomedical engineering online
Tracking points in ultrasound (US) videos can be especially useful to characterize tissues in motion. Tracking algorithms that analyze successive video frames, such as variations of Optical Flow and Lucas-Kanade (LK), exploit frame-to-frame temporal ...

AI and machine learning ethics, law, diversity, and global impact.

The British journal of radiology
Artificial intelligence (AI) and its machine learning (ML) algorithms are offering new promise for personalized biomedicine and more cost-effective healthcare with impressive technical capability to mimic human cognitive capabilities. However, widesp...