AIMC Topic: Animals

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Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

Neuron
A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neu...

The effect of sensory feedback topology on the entrainment of a neural oscillator with a compliant foil for swimming systems.

Bioinspiration & biomimetics
The sensorimotor system of fish endows them with remarkable swimming performance that is unmatched by current underwater robotic vehicles. To close the gap between the capabilities of fish and the capabilities of underwater vehicles engineers are inv...

Feature Selection for High-Dimensional and Imbalanced Biomedical Data Based on Robust Correlation Based Redundancy and Binary Grasshopper Optimization Algorithm.

Genes
The training machine learning algorithm from an imbalanced data set is an inherently challenging task. It becomes more demanding with limited samples but with a massive number of features (high dimensionality). The high dimensional and imbalanced dat...

Stray energy transfer in single-incision robotic surgery.

Surgical endoscopy
INTRODUCTION: Stray energy transfer from surgical monopolar radiofrequency energy instruments can cause unintended thermal injuries during laparoscopic surgery. Single-incision laparoscopic surgery transfers more stray energy than traditional laparos...

Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells.

International journal of environmental research and public health
The emergence of new technologies to incorporate and analyze data with high-performance computing has expanded our capability to accurately predict any incident. Supervised Machine learning (ML) can be utilized for a fast and consistent prediction, a...

Amur tiger stripes: individual identification based on deep convolutional neural network.

Integrative zoology
The automatic individual identification of Amur tigers (Panthera tigris altaica) is important for population monitoring and making effective conservation strategies. Most existing research primarily relies on manual identification, which does not sca...

Single-Cell Classification Using Mass Spectrometry through Interpretable Machine Learning.

Analytical chemistry
The brain consists of organized ensembles of cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries that control the executive functions of an organism. However, the relationships between chemical heterogeneity, c...

Learning to localize sounds in a highly reverberant environment: Machine-learning tracking of dolphin whistle-like sounds in a pool.

PloS one
Tracking the origin of propagating wave signals in an environment with complex reflective surfaces is, in its full generality, a nearly intractable problem which has engendered multiple domain-specific literatures. We posit that, if the environment a...

NeuroConstruct-based implementation of structured-light stimulated retinal circuitry.

BMC neuroscience
BACKGROUND: Retinal circuitry provides a fundamental window to neural networks, featuring widely investigated visual phenomena ranging from direction selectivity to fast detection of approaching motion. As the divide between experimental and theoreti...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

Pharmacological research
In personalized medicine, many factors influence the choice of compounds. Hence, the selection of suitable medicine for patients with non-small-cell lung cancer (NSCLC) is expensive. To shorten the decision-making process for compounds, we propose a ...