AIMC Topic: Humans

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Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training.

Scientific reports
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fas...

A transformer-based network with second-order pooling for motor imagery EEG classification.

Journal of neural engineering
. Electroencephalography (EEG) signals can reflect motor intention signals in the brain. In recent years, motor imagery (MI) based brain-computer interfaces (BCIs) have attracted the attention of neuroinformatics researchers. Numerous deep learning m...

Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.

Physiological measurement
. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant problem in treating patients using mechanical ventilation. If not handled timely, it can pose risk of s...

In-silico CT simulations of deep learning generated heterogeneous phantoms.

Biomedical physics & engineering express
Current virtual imaging phantoms primarily emphasize geometric accuracy of anatomical structures. However, to enhance realism, it is also important to incorporate intra-organ detail. Because biological tissues are heterogeneous in composition, virtua...

BIScreener: enhancing breast cancer ultrasound diagnosis through integrated deep learning with interpretability.

Analytical methods : advancing methods and applications
Breast cancer is the leading cause of death among women worldwide, and early detection through the standardized BI-RADS framework helps physicians assess the risk of malignancy and guide appropriate diagnostic and treatment decisions. In this study, ...

An investigation of multimodal EMG-EEG fusion strategies for upper-limb gesture classification.

Journal of neural engineering
. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses. Prevailing research into classifying electromyographic (EMG) muscular data or electroencephalographic (EEG) brain data for this purpose is often lim...

Decoding tissue complexity: multiscale mapping of chemistry-structure-function relationships through advanced visualization technologies.

Journal of materials chemistry. B
Comprehensively acquiring biological tissue information is pivotal for advancing our understanding of biological systems, elucidating disease mechanisms, and developing innovative clinical strategies. Biological tissues, as nature's archetypal biomat...

Nondisruptive inducible labeling of ER-membrane contact sites using the Lamin B receptor.

PLoS biology
Membrane contact sites (MCSs) are areas of close proximity between organelles that allow the exchange of material, among other roles. The endoplasmic reticulum (ER) has MCSs with a variety of organelles in the cell. MCSs are dynamic, responding to ch...

Rule-based AI automated adaptive treatment planning for image guided cervical cancer brachytherapy.

Brachytherapy
BACKGROUND AND PURPOSE: A rule-based AI system for automated adaptive treatment planning for image guided adaptive brachytherapy (IGABT) of locally advanced cervical cancer (LACC) was developed at Erasmus MC, and internally and externally validated b...

Classification of commercial districts based on predicting the survival rate of food service market in Seoul.

PloS one
The chronic small-business closure has emerged as a critical economic issue in South Korea, considering more than half of businesses have been closed within three years. While some previous literature has analyzed the causes and their negative impact...