AIMC Topic: Algorithms

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Fish-inspired robotic algorithm: mimicking behaviour and communication of schooling fish.

Bioinspiration & biomimetics
This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, ali...

Neuromorphic sequence learning with an event camera on routes through vegetation.

Science robotics
For many robotics applications, it is desirable to have relatively low-power and efficient onboard solutions. We took inspiration from insects, such as ants, that are capable of learning and following routes in complex natural environments using rela...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

Journal of autism and developmental disorders
PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic crite...

An Interventional Radiologist's Primer of Critical Appraisal of Artificial Intelligence Research.

Journal of vascular and interventional radiology : JVIR
Recent advances in artificial intelligence (AI) are expected to cause a significant paradigm shift in all digital data-driven aspects of information gain, processing, and decision making in both clinical healthcare and medical research. The field of ...

External validation of deep learning-based automated detection algorithm for chest radiograph: practical issues in outpatient clinic.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: There have been no reports on diagnostic performance of deep learning-based automated detection (DLAD) for thoracic diseases in real-world outpatient clinic.

Validation of a Deep Learning Algorithm for Continuous, Real-Time Detection of Atrial Fibrillation Using a Wrist-Worn Device in an Ambulatory Environment.

Journal of the American Heart Association
BACKGROUND: Wearable devices may be useful for identification, quantification and characterization, and management of atrial fibrillation (AF). To date, consumer wrist-worn devices for AF detection using photoplethysmography-based algorithms perform ...

AC-Faster R-CNN: an improved detection architecture with high precision and sensitivity for abnormality in spine x-ray images.

Physics in medicine and biology
In clinical medicine, localization and identification of disease on spinal radiographs are difficult and require a high level of expertise in the radiological discipline and extensive clinical experience. The model based on deep learning acquires cer...

A Deep Learning Approach for Neuronal Cell Body Segmentation in Neurons Expressing GCaMP Using a Swin Transformer.

eNeuro
Neuronal cell body analysis is crucial for quantifying changes in neuronal sizes under different physiological and pathologic conditions. Neuronal cell body detection and segmentation mainly rely on manual or pseudo-manual annotations. Manual annotat...

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Frontiers in endocrinology
BACKGROUND: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented.

Research on cloud manufacturing service recommendation based on graph neural network.

PloS one
There are an increasing number of manufacturing service resources appeared on the cloud manufacturing (CMfg) service platform recently, which leads to a serious information overloading problem to the enterprises that need these resources. To tackle t...