AIMC Topic: Algorithms

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Mandibular and dental measurements for sex determination using machine learning.

Scientific reports
The present study tested the combination of mandibular and dental dimensions for sex determination using machine learning. Lateral cephalograms and dental casts were used to obtain mandibular and mesio-distal permanent teeth dimensions, respectively....

3D printing of an artificial intelligence-generated patient-specific coronary artery segmentation in a support bath.

Biomedical materials (Bristol, England)
Accurate segmentation of coronary artery tree and personalized 3D printing from medical images is essential for CAD diagnosis and treatment. The current literature on 3D printing relies solely on generic models created with different software or 3D c...

A hybrid 1D CNN-BiLSTM model for epileptic seizure detection using multichannel EEG feature fusion.

Biomedical physics & engineering express
Epilepsy, a chronic non-communicable disease is characterized by repeated unprovoked seizures, which are transient episodes of abnormal electrical activity in the brain. While Electroencephalography (EEG) is considered as the gold standard for diagno...

Learning spatio-temporal patterns with Neural Cellular Automata.

PLoS computational biology
Neural Cellular Automata (NCA) are a powerful combination of machine learning and mechanistic modelling. We train NCA to learn complex dynamics from time series of images and Partial Differential Equation (PDE) trajectories. Our method is designed to...

Development of new materials for electrothermal metals using data driven and machine learning.

PloS one
After adopting a combined approach of data-driven methods and machine learning, the prediction of material performance and the optimization of composition design can significantly reduce the development time of materials at a lower cost. In this rese...

Crossmixed convolutional neural network for digital speech recognition.

PloS one
Digital speech recognition is a challenging problem that requires the ability to learn complex signal characteristics such as frequency, pitch, intensity, timbre, and melody, which traditional methods often face issues in recognizing. This article in...

E-BabyNet: Enhanced Action Recognition of Infant Reaching in Unconstrained Environments.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine vision and artificial intelligence hold promise across healthcare applications. In this paper, we focus on the emerging research direction of infant action recognition, and we specifically consider the task of reaching which is an important d...

Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.

Molecular psychiatry
With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques ...

Uncertain prediction of deformable image registration on lung CT using multi-category features and supervised learning.

Medical & biological engineering & computing
The assessment of deformable registration uncertainty is an important task for the safety and reliability of registration methods in clinical applications. However, it is typically done by a manual and time-consuming procedure. We propose a novel aut...

TGIN: Document-level event extraction with two-phase graph inference network.

Neural networks : the official journal of the International Neural Network Society
Document-level event extraction aims to extract event records from a whole document that contain numerous entities scattered across multiple sentences. Efficiently modeling the interactions among these entities is crucial. However, previous methods s...