AIMC Topic: Algorithms

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Newborn Pulse-Oximetry Screening.

Clinics in perinatology
Pulse oximetry screening (POS) is a noninvasive tool for the detection of critical congenital heart defects (CCHD) that has moderate sensitivity and high specificity. It is readily accepted by parents and health care professional and has significantl...

Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks.

Scientific reports
Accurate and efficient analysis of Electroencephalogram (EEG) signals is crucial for applications like neurological diagnosis and Brain-Computer Interfaces (BCI). Traditional methods often fall short in capturing the intricate temporal dynamics inher...

Prediction of birthweight with early and mid-pregnancy antenatal markers utilising machine learning and explainable artificial intelligence.

Scientific reports
Low birthweight (LBW) is a significant health challenge worldwide, as these neonates experience both short- and long-term disabilities. Factors affecting maternal and fetal health during early to mid-pregnancy can greatly influence fetal development....

Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning.

Scientific reports
Soil water retention is a critical aspect of water conservation. To quantitatively assess the Soil Water-Holding Capacity (SWHC), this study focused on a typical wild fruit forest in Xinjiang, China. The spectral characteristics of the forest canopy ...

An interactive information based DCNN-BiLSTM model with dual attention mechanism for facial expression recognition.

Scientific reports
Human's facial expressions and emotions have direct impact on their action and decision-making abilities. Basic CNN models are complexity of speeding up the operation to minimize the complexity. In this paper, we have proposed a Deep Convolutional Ne...

Enhancing breast cancer classification using a deep sparse wavelet autoencoder approach.

Scientific reports
As digital imaging technology advances, accurate classification of 2D breast cancer images becomes increasingly crucial for early detection and staging. This paper introduces a novel classification approach that integrates deep learning, sparse codin...

Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.

Journal of proteome research
A major challenge in mass-spectrometry-based metaproteomics is accurately identifying and quantifying biological functions across the full taxonomic lineage of microorganisms. This issue stems from what we refer to as the "shared confidently identifi...

A densely connected framework for cancer subtype classification.

BMC bioinformatics
BACKGROUND: Reliable identification of cancer subtypes is crucial for devising personalized treatment strategies. Integrating multi-omics data has proven to be an effective method for analyzing cancer subtypes. By combining molecular information acro...

Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks.

BMC medical imaging
BACKGROUND: The skull is highly durable and plays a significant role in sex determination as one of the most dimorphic bones. The facial canal (FC), a clinically significant canal within the temporal bone, houses the facial nerve. This study aims to ...

Development of an artificial intelligence algorithm for automated surgical gestures annotation.

Journal of robotic surgery
Surgical gestures analysis is a promising method to assess surgical procedure quality, but manual annotation is time-consuming. We aimed to develop a recurrent neural network for automated surgical gesture annotation using simulated robot-assisted ra...