AIMC Topic: Algorithms

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Machine-learning based prediction of Cushing's syndrome in dogs attending UK primary-care veterinary practice.

Scientific reports
Cushing's syndrome is an endocrine disease in dogs that negatively impacts upon the quality-of-life of affected animals. Cushing's syndrome can be a challenging diagnosis to confirm, therefore new methods to aid diagnosis are warranted. Four machine-...

WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans.

PLoS computational biology
An important model system for understanding genes, neurons and behavior, the nematode worm C. elegans naturally moves through a variety of complex postures, for which estimation from video data is challenging. We introduce an open-source Python packa...

Hybrid Convolutional Neural Network for Localization of Epileptic Focus Based on iEEG.

Neural plasticity
Epileptic focus localization by analysing intracranial electroencephalogram (iEEG) plays a critical role in successful surgical therapy of resection of the epileptogenic lesion. However, manual analysis and classification of the iEEG signal by clinic...

The influence of random number generation in dissipative particle dynamics simulations using a cryptographic hash function.

PloS one
The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DPD) calculations in parallel, usually on distributed memory systems. In this research, we reduced the computational cost of the TEA hash function and i...

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform.

Journal of the American Heart Association
Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinical...

ELVISort: encoding latent variables for instant sorting, an artificial intelligence-based end-to-end solution.

Journal of neural engineering
The growing number of recording sites of silicon-based probes means that an increasing amount of neural cell activities can be recorded simultaneously, facilitating the investigation of underlying complex neural dynamics. In order to overcome the cha...

Edge deep learning for neural implants: a case study of seizure detection and prediction.

Journal of neural engineering
Implanted devices providing real-time neural activity classification and control are increasingly used to treat neurological disorders, such as epilepsy and Parkinson's disease. Classification performance is critical to identifying brain states appro...

RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

F1000Research
Non-coding RNAs (ncRNAs) are important players in the cellular regulation of organisms from different kingdoms. One of the key steps in ncRNAs research is the ability to distinguish coding/non-coding sequences. We applied seven machine learning algor...

Computational Logistics for Container Terminal Handling Systems with Deep Learning.

Computational intelligence and neuroscience
Container terminals are playing an increasingly important role in the global logistics network; however, the programming, planning, scheduling, and decision of the container terminal handling system (CTHS) all are provided with a high degree of nonli...